Alice (Formerly ActiveFence)

Description We are hiring a Principal Data Scientist for the Data Science group, reporting directly to the VP Engineering. This is a senior individual-contributor leadership role: you own the technical direction and architecture of what the group ships - real-time inference at scale, automated red-teaming of GenAI systems, and the Databricks/Spark data platform underneath - and you lead the hardest projects end to end, hands on in the code. What you'll own A large Python, Rust, and PySpark monorepo, dozens of production services and shared libraries, across three connected domains: Content-moderation inference at scale Real-time, multi-tenant detection across text, image, video, and audio - hate speech, CSAM, nudity, child grooming, extremism, PII, prompt injection, age estimation, and more - served through our in-house ActiveServe framework over NVIDIA Triton and a Rust detection service, on latency-sensitive, SLA-bound, customer-facing traffic with per-customer custom models. GenAI safety and red-teaming Automated red-teaming that attacks customers' LLM applications with a research-driven attack taxonomy and measures attack-success rate, alongside the defensive side - LLM-as-judge escalation to cut false positives, and the tooling that authors and refines moderation policies - built on a multi-provider LLM foundation (Bedrock, Anthropic, OpenAI, Gemini, xAI Grok). Data platform and MLOps An end-to-end lakehouse and MLOps stack on Databricks - bronze/silver/gold ingestion, PySpark pipelines, and model training, versioning, and promotion through MLflow / Unity Catalog into Triton serving - with the performance-critical hot paths engineered in Rust (PyO3/maturin) for sub-millisecond, high-QPS matching and detection. What you'll do • Own the GenAI safety roadmap - decide what we build with LLMs and what we build around them: guardrails and LLM-as-judge adjudication, prompt-injection and jailbreak detection, policy authoring, and the automated red-teaming that measures attack-success rate against customers' applications. Choose which model families and providers we use, fine-tune, or retire, and what each has to prove before it reaches customer traffic. • Own how we evaluate GenAI systems - benchmark and dataset design over real production traffic, LLM-jury labeling protocols, multilingual, multi-turn, and multimodal coverage, calibration and threshold selection, and the error analysis that turns a metric into a fix. Run the evaluations that separate a real shift in what these models can do from a launch post, and keep quality honest in production as traffic, prompts, and attacks drift. • Lead the hardest GenAI work end to end, and grow the craft - take the ambiguous, high-stakes projects from framing through prototype, offline evaluation, shadow traffic, and rollout; mentor data scientists and ML engineers through design, experiment, and model review; and translate model behavior into what Product and customers care about: accuracy, latency, cost, and enterprise readiness. Requirements What we're looking for • ML technical leadership - a proven tech lead, senior data scientist, or ML engineer who has taken multi-person, multi-quarter ML initiatives from framing to production without formal authority, with strong Python and the written communication to make the case in a design or an evaluation. • Deep understanding of LLM technology - how these models are trained, adapted, and served, what prompting, fine-tuning, RAG, and agentic patterns each buy you, where they fail, and how to measure quality, latency, and cost. • AI-augmented engineering - deep, daily fluency with an AI coding assistant (Claude Code, Cursor, or Codex), with the judgment to raise the whole team's leverage and set how these tools are used well. About Alice Alice is a trust, safety, and security company built for the AI era. We safeguard the communicative technologies people use to create, collaborate, and interact- whether with each other or with machines. In a world where AI has fundamentally changed the nature of risk, Alice provides end-to-end coverage across the entire AI lifecycle. We support frontier model labs, enterprises, and UGC platforms with a comprehensive suite of solutions: from model hardening evaluations and pre-deployment red-teaming to runtime guardrails and ongoing drift detection. Alice is widely considered a global leader in online safety and AI security. We have some of the most forward-thinking and passionate minds in the world working to safeguard over 3 billion users across the largest AI and tech platforms. If you're creative and driven to secure the future of AI, we want to hear from you!

Description Alice's RL Environments team builds adversarial environments that the world's leading AI labs use to test and train their most capable agents. Each environment is a working replica of a real system with an attack planted inside it. A verifier decides whether the agent held up. All of it runs on AgenticVerse, our platform for building, running, and reviewing RL environments. AgenticVerse is a full-fledged, production-grade SaaS application. A large and fast-growing community of researchers works in it every day. We're looking for a Senior Full-Stack Engineer to own AgenticVerse as a product, and to build the digital twins our environments are made of. What you'll do AgenticVerse • Own the AgenticVerse application end to end: frontend, backend, data model, and APIs • Build the workflows researchers live in: authoring tasks, launching runs, managing gyms, and reviewing results • Make a run readable at a glance: traces, verifier results, and where the agent went wrong • Hold a production bar: performance, reliability, access control, and observability as the user base grows • Take features from design to production, and talk to the researchers who use them Digital twins • Build digital twins of real products: web apps an agent can't tell apart from the real thing • Build the full stack behind each one: the UI, a real API backend, and the state that persists across a run • Expose every action the agent takes as an event the verifier can grade Requirements What we're looking for • 6+ years as a full-stack engineer, building production SaaS • BSc in Computer Science or a related field, preferably from a leading university • Strong TypeScript and React, and a backend language (Python preferred) • Experience designing APIs and data models for multi-user applications • Production experience with Docker and cloud infrastructure (AWS preferred) • High autonomy in an undefined space. You take a loose problem and come back with working code • Fluent written and spoken English Advantage • Hands-on AI engineering: building with LLMs, agents, or evaluations • Experience building developer tools or internal platforms • Experience with Kubernetes • Background in security, red teaming, or trust and safety About Alice Alice is a trust, safety, and security company built for the AI era. We safeguard the communicative technologies people use to create, collaborate, and interact- whether with each other or with machines. In a world where AI has fundamentally changed the nature of risk, Alice provides end-to-end coverage across the entire AI lifecycle. We support frontier model labs, enterprises, and UGC platforms with a comprehensive suite of solutions: from model hardening evaluations and pre-deployment red-teaming to runtime guardrails and ongoing drift detection. Alice is widely considered a global leader in online safety and AI security. We have some of the most forward-thinking and passionate minds in the world working to safeguard over 3 billion users across the largest AI and tech platforms. If you're creative and driven to secure the future of AI, we want to hear from you!

Description Alice is a leading platform for Trust & Safety teams worldwide, leveraging cutting‑edge AI and world‑class expertise to protect users from the widest spectrum of online harms. By continuously collecting and analyzing data, our solutions ensure customers stay two steps ahead of bad actors in an ever‑changing threat landscape. We’re seeking an outstanding Backend Engineer with a Generative AI orientation to join our research team. We are building a new AI Platform from scratch to standardize AI development methods, ensure excellence and efficiency, and deliver robust, scalable, and compliant AI capabilities. This platform will handle GenAI models deployment, prompt management, data filtering, logging, and monitoring, centrally, so individuals can focus on their own business-specific logic. Key Responsibilities • Build and maintain CI/CD pipelines that support fast, reliable integration and deployment of GenAI systems across complex environments, including orchestrating multiple models/agents and MCP clients/servers. • Develop, deploy and integrate AI solutions and agentic frameworks, creating both command‑line tools and interactive notebooks that support our team’s research and workflow automation needs. • Build and manage data pipelines and databases (SQL) for large‑scale data handling, automating data collection and curation (e.g., adversarial prompts for model red-teaming) to support AI training and evaluation. • Integrate research into production by implementing the latest generative AI advancements (including white‑box LLM development), integrating different models and agents, and developing evaluation frameworks (e.g., agentic reasoning tests) as part of our automated workflows. • Integration & Orchestration: Integrate dockerized environments (e.g., Harbor format) into internal training frameworks, optimizing reset/statefulness semantics, concurrency, and throughput ceilings • Deploy GenAI models from repositories such as HuggingFace onto our AWS platform, connect them to data pipelines, and automate end‑to‑end processes for prompt generation, labeling, and response evaluation. Requirements Must-to-have • B.Sc. in Computer Science, Computer Engineering, or a related field (or equivalent hands‑on experience). • 5+ years of experience delivering large‑scale, high‑performance systems on AWS, with an emphasis on orchestrating data pipelines and AI workflows in production environments. • Expertise in scripting and automation using Python and shell; proven ability to write clean IaC and CI/CD pipelines. • Strong understanding of Linux systems, networking, and distributed system design. • Ability to break down monolithic systems into scalable, loosely coupled services and microservices. • Strong cross‑functional communication and collaboration skills, with a DevOps mindset to drive best practices across teams. • Hands‑on experience deploying and integrating generative AI models (e.g., large language models or other AI/ML models) in production. • Hands‑on experience deploying MCP clients/servers and integrating them into automated AI workflows. Nice-to-Have • M.Sc. in Computer Science, Computer Engineering, or a related field. • Experience with large‑scale cluster management or HPC scheduling tools (e.g., Slurm). • Knowledge of advanced observability and monitoring tools such as Prometheus and Grafana. • Experience with cloud cost optimization (FinOps concepts) and exposure to infrastructure security tools or configuration management for compliance. • Hands‑on experience working with A2A protocol. Alice is the leading provider of security and safety solutions for online experiences, safeguarding more than 3 billion users, top foundation models, and the world’s largest enterprises and tech platforms every day. As a trusted ally to major technology firms and Fortune 500 brands that build user-generated and GenAI products, Alice empowers security, AI, and policy teams with low-latency Real-Time Guardrails and a continuous Red Teaming program that pressure-tests systems with adversarial prompts and emerging threat techniques. Powered by deep threat intelligence, unmatched harmful-content detection, and coverage of 117+ languages, Alice enables organizations to deliver engaging and trustworthy experiences at global scale while operating safely and responsibly across all threat landscapes. About Alice Alice is a trust, safety, and security company built for the AI era. We safeguard the communicative technologies people use to create, collaborate, and interact- whether with each other or with machines. In a world where AI has fundamentally changed the nature of risk, Alice provides end-to-end coverage across the entire AI lifecycle. We support frontier model labs, enterprises, and UGC platforms with a comprehensive suite of solutions: from model hardening evaluations and pre-deployment red-teaming to runtime guardrails and ongoing drift detection. Alice is widely considered a global leader in online safety and AI security. We have some of the most forward-thinking and passionate minds in the world working to safeguard over 3 billion users across the largest AI and tech platforms. If you're creative and driven to secure the future of AI, we want to hear from you!

Description We are hiring an Engineering Manager to own and grow the Data Science group - the R&D team behind Alice's security and safety AI models and the data platform that powers them. You will lead a multidisciplinary team of ML engineers, data scientists, and software engineers who ship real-time inference at scale, automated red-teaming of GenAI systems, and the Databricks/Spark data platform underneath. This is a hands-on people-leadership role: you set technical direction, are accountable for delivery and quality, and you build and grow the team. What your team owns The group is responsible for a large Python + Rust + PySpark monorepo (dozens of production services and shared libraries) spanning three connected domains: 1. Content-moderation inference at scale Real-time, multi-tenant detection across text, image, video, and audio - hate speech, CSAM, nudity, child grooming, extremism, PII, prompt injection, age estimation, and more - served through an in-house ActiveServe framework over NVIDIA Triton and a Rust detection monolith, on latency-sensitive, SLA-bound, customer-facing traffic with per-customer custom models. 2. GenAI safety & red-teaming Automated red-teaming that attacks customers' LLM applications with a research-driven attack taxonomy and measures attack-success rate, alongside the defensive side - LLM-as-judge escalation to cut false positives and the tooling that authors and refines moderation policies - built on a multi-provider LLM foundation (Bedrock, Anthropic, OpenAI, Gemini, xAI Grok) and forming Alice's leading edge into agentic-AI safety. 3. Data platform & MLOps An end-to-end lakehouse and MLOps stack on Databricks - bronze/silver/gold ingestion, PySpark pipelines, and model training, versioning, and promotion through MLflow / Unity Catalog into Triton serving - with the performance-critical hot paths engineered in Rust (PyO3/maturin) for sub-millisecond, high-QPS matching and detection. What you'll do • Lead and grow the team - mentor ML engineers, data scientists, and software engineers, and own hiring, onboarding, 1:1s, career development, and performance. • Set direction and deliver - set technical direction and standards, turn company and product goals into a prioritized roadmap, and own the quality, reliability, and delivery of the systems above across parallel workstreams. • Champion excellence and partnership - stay hands-on to review designs and unblock the team, drive engineering excellence (testing, observability, CI/CD, on-call, cost/latency), keep the team at the state of the art in ML, LLMs, and GenAI safety, and partner with Product, Platform, and GenAI-safety stakeholders. Leadership competencies • People-first: builds trust, grows engineers, and creates a healthy, inclusive, high-ownership culture. • Outcome-oriented: drives clarity, sets priorities, and delivers under ambiguity without micromanaging. • Technical credibility: earns the team's respect through sound judgment on architecture and trade-offs. • Systems thinker: balances short-term delivery against long-term platform health, cost, and tech debt. Requirements What we're looking for (must-have) • Leadership & communication - a proven people manager of engineering or data-science teams (or a strong tech lead ready to step into formal management), with excellent communication and stakeholder management. • Hands-on engineering and ML at scale - strong production Python and software-engineering background with solid ML / data-science foundations (training, evaluation, deployment, monitoring), running services at scale on AWS and Kubernetes and large-scale data on Spark/PySpark and a lakehouse (Databricks or equivalent). • AI-augmented engineering - deep, daily fluency with an AI coding assistant (Claude Code, Cursor, or Codex), with the judgment to raise the whole team's leverage and set how these tools are used well. Nice to have • Experience with LLMs / GenAI in production - prompting, evaluation, guardrails, red-teaming, or agentic systems. • Experience with model serving on NVIDIA Triton (or similar) and the MLflow / Unity Catalog lifecycle. • Familiarity with Rust and Python/Rust interop (PyO3/maturin) for performance-critical paths. • Background in GenAI safety and security, content moderation, or another domain where model quality has real-world stakes. • Experience with event-driven architectures (Kafka, SQS) and Infrastructure-as-Code (Terraform). About Alice Alice is a trust, safety, and security company built for the AI era. We safeguard the communicative technologies people use to create, collaborate, and interact- whether with each other or with machines. In a world where AI has fundamentally changed the nature of risk, Alice provides end-to-end coverage across the entire AI lifecycle. We support frontier model labs, enterprises, and UGC platforms with a comprehensive suite of solutions: from model hardening evaluations and pre-deployment red-teaming to runtime guardrails and ongoing drift detection. Alice is widely considered a global leader in online safety and AI security. We have some of the most forward-thinking and passionate minds in the world working to safeguard over 3 billion users across the largest AI and tech platforms. If you're creative and driven to secure the future of AI, we want to hear from you!

Description Alice is at the forefront of a shift in online safety. As Big Tech moves beyond reactive moderation, Alice is building the agentic future of Trust & Safety. We are hiring a Director of Product to close the gap between our Trust & Safety expertise and the automated, repeatable products the world's largest platforms now need. This is a high-impact leadership role focused on incubating new ideas, pushing from 0 to 1, and productizing what works. You will turn bespoke moderation workflows and investigation methodologies into a portfolio of repeatable, data-driven offerings that let global platforms run agentic safety systems at volume. This role is not red teaming and it is not research. It is execution and scale. You will work closely with the pod leadership to capture domain expertise and embed it into the Alice product suite. Core responsibilities • Productization strategy. Identify high-value Trust & Safety & Security workflows inside Big Tech environments and architect their transformation into standardized product offerings that hold up at platform volume. • Maintain the data moat. Define Alice's data assets as the durable differentiation across all of the company's offerings, services and product lines. • Agentic moderation. Lead the product roadmap for the transition from manual and basic-automated moderation to agentic systems capable of autonomous investigation and enforcement. • Scaling for Big Tech. Design offerings for the infrastructure and policy requirements of big tech platforms like -high throughput, low friction to adopt. • Deliver bespoke projects. Secondary, but real: lead demand and learn from existing and incoming projects, covering the full cycle of requirement collection, development and delivery. Requirements • Proven track record in product management or leadership within the Trust & Safety or Security domains, with a demonstrated ability to lead cross-functional teams • Strategic product leadership: experience leading cross-functional teams to deliver 1-to-N product growth, with a focus on repeatability, efficiency and market fit • T&S scaling: a proven track record of taking complex service-based operations or internal tools and scaling them into revenue-generating, production-ready products • Big Tech literacy: deep understanding of Trust & Safety ecosystems, policy constraints and operational friction points within major platforms • Agentic systems: strong conceptual and practical understanding of how LLM-driven agents can be deployed for content moderation and deep-dive investigations • Entrepreneurial execution: able to operate at a high strategic level while holding the technical depth to judge product feasibility • Communication: mastery in distilling complex technical capabilities into clear, value-driven narratives for senior stakeholders at Fortune 500 companies About Alice Alice is a trust, safety, and security company built for the AI era. We safeguard the communicative technologies people use to create, collaborate, and interact- whether with each other or with machines. In a world where AI has fundamentally changed the nature of risk, Alice provides end-to-end coverage across the entire AI lifecycle. We support frontier model labs, enterprises, and UGC platforms with a comprehensive suite of solutions: from model hardening evaluations and pre-deployment red-teaming to runtime guardrails and ongoing drift detection. Alice is widely considered a global leader in online safety and AI security. We have some of the most forward-thinking and passionate minds in the world working to safeguard over 3 billion users across the largest AI and tech platforms. If you're creative and driven to secure the future of AI, we want to hear from you!

Description Alice is seeking an experienced Malware Research Team Leader to lead a team of malware researchers, combining hands-on research with people leadership. This role presents an opportunity to lead an established team, strengthening its skills through ongoing training and guidance while ensuring high-quality deliverables. The position balances managerial responsibilities with hands-on technical work (approximately 50% each). The ideal candidate demonstrates a positive, proactive attitude and excels as a reliable team player. Key Responsibilities: • Mentor and manage a team of malware researchers, including recruitment • Conduct short, focused malware research under tight timelines • Detect and document emerging malware trends • Evaluate and enhance team accuracy and performance • Regularly share knowledge with team members and collaborate across teams and departments • Continuously improve malware analysis and review processes • Develop automation processes for malware identification at scale Requirements Must-Have • Management experience - managing at least 2 employees for at least 2 years, with experience in recruiting and training • At least 3 years of proven experience in one of the following: Malware research Reverse engineering Penetration testing In-depth SOC/IR investigations Application security • Strong grasp of object-oriented programming and the ability to trace execution flow through code • Familiarity with multiple languages (Java, C/C++, JavaScript, Python) • Familiarity with static and dynamic research tools such as JADX, Frida, and network debuggers • Understanding of network communications and protocols Nice-to-Have: • Degree in Computer Science, Software Engineering, Electrical Engineering, or a similar field • Proven experience managing a team of more than 5 employees • Experience with disassemblers and native debuggers (e.g., Ghidra, IDA Pro, JEB, LLDB, GDB, x86dbg) • Proficiency with HTTP debuggers, MITM tools, and network analyzers (e.g., Fiddler, HTTP Toolkit, Burp Suite, Wireshark, Little Snitch, mitmproxy) • Development experience in Java, Kotlin, Python, JavaScript, or C/C++ • Familiarity with multiplatform frameworks such as Flutter, React Native, or Unity About Alice Alice is a trust, safety, and security company built for the AI era. We safeguard the communicative technologies people use to create, collaborate, and interact- whether with each other or with machines. In a world where AI has fundamentally changed the nature of risk, Alice provides end-to-end coverage across the entire AI lifecycle. We support frontier model labs, enterprises, and UGC platforms with a comprehensive suite of solutions: from model hardening evaluations and pre-deployment red-teaming to runtime guardrails and ongoing drift detection. Alice is widely considered a global leader in online safety and AI security. We have some of the most forward-thinking and passionate minds in the world working to safeguard over 3 billion users across the largest AI and tech platforms. If you're creative and driven to secure the future of AI, we want to hear from you!

Description We are seeking a highly technical, hands-on Principal AI Research Cybersecurity Scientist to drive fast-paced research in frontier AI models, benchmarking, and evaluation. The ideal candidate combines strong research credentials with exceptional engineering capabilities and a proven ability to execute rapid research cycles, moving quickly from identifying research questions to building prototypes, running experiments, and delivering actionable results. The role requires deep expertise in LLMs, foundation models, reasoning, agents, and model evaluation, alongside the ability to translate complex customer challenges into measurable research outcomes. Key Responsibilities • Conduct hands-on research in frontier AI models, reasoning, agents, and multimodal systems. • Design, implement, and iterate on AI benchmarks, evaluation frameworks, and experimental pipelines. • Execute short, high-impact research cycles, rapidly moving from hypotheses to experiments, prototypes, and validated findings. • Identify model limitations, evaluation gaps, and emerging research opportunities. • Work directly with customers and technical stakeholders to translate complex challenges into actionable research. • Collaborate with engineering and product teams to turn research findings into practical solutions. Requirements Qualifications • PhD or MSc in Computer Science, AI, Machine Learning, or a related field, with strong relevant research experience. • Strong publication record at leading AI/ML conferences such as NeurIPS, ICML, ICLR, ACL, or equivalent venues. • Exceptional hands-on technical capabilities, including advanced Python, PyTorch, and experience building and evaluating complex AI systems. • Proven ability to independently design, implement, and execute research experiments within short development cycles. • Deep understanding of LLMs, foundation models, benchmarking, and evaluation methodologies. • Experience with frontier AI labs such as OpenAI, Anthropic, or Google DeepMind is a strong advantage. • Strong analytical and communication skills, with the ability to operate effectively in a fast-paced, customer-driven research environment. Preferred Qualifications • Experience with AI for Cybersecurity, including autonomous security agents, vulnerability research, penetration-testing automation, or security operations. • Experience with Security of AI, including LLM red teaming, adversarial machine learning, prompt injection, and agentic AI security. • Familiarity with cybersecurity tools and environments such as CTFs, sandboxed exploitation environments, static/dynamic code analysis, and security testing frameworks. • Experience developing cybersecurity benchmarks or evaluating frontier models on complex security-related tasks. About Alice Alice is a trust, safety, and security company built for the AI era. We safeguard the communicative technologies people use to create, collaborate, and interact- whether with each other or with machines. In a world where AI has fundamentally changed the nature of risk, Alice provides end-to-end coverage across the entire AI lifecycle. We support frontier model labs, enterprises, and UGC platforms with a comprehensive suite of solutions: from model hardening evaluations and pre-deployment red-teaming to runtime guardrails and ongoing drift detection. Alice is widely considered a global leader in online safety and AI security. We have some of the most forward-thinking and passionate minds in the world working to safeguard over 3 billion users across the largest AI and tech platforms. If you're creative and driven to secure the future of AI, we want to hear from you!

Description Alice secures AI apps, agents and models from build to production. Enterprises already run agents that talk to their customers, read their email and call their internal tools. Every conversation and every connection can be a way in for an attacker, or the point where an agent goes rogue. You find out how those agents break, on the stacks enterprises actually use, before they cause harm. You will be the first AI security researcher on the product team, reporting to the Director of GenAI Products. Your research becomes guardrails and red teaming tests in the Alice platform, proof customers can act on, and research our marketing team publishes. It also feeds the threat intelligence we deliver. You choose the questions, guided by what enterprises are deploying right now and by the wider research Alice does with the foundation model labs. Key Responsibilities • Research emerging agent risks. Study how agents fail when they talk to users, read untrusted content, call tools, share memory, act autonomously and work with other agents. That covers indirect prompt injection, tool and MCP misuse, data exfiltration, memory poisoning, privilege escalation across agents and unsafe autonomous actions. • Test and prove. Build the environments and experiments that show whether a risk is real, how often it happens and under which conditions. Work on the stacks enterprises use: agent frameworks, MCP servers, workflow tools and AI gateways. Build the sandboxes, detectors and graders that catch failures, and turn each one into a regression test anyone can rerun. Measure how often and how severely agents misbehave, and how that shifts across models, tools and harnesses. Report results with the numbers behind them, so others can rerun and trust them. • Shape the platform. Work with the product team to turn your findings into new guardrails and red-team tests in the Alice platform. • Inform go-to-market and threat intelligence. Share findings and evidence with sales, marketing and Alice's threat intelligence teams, so they can explain new risks to customers with proof behind them. • Publish. Turn research into technical posts, reports and talks with the marketing team, written to hold up with security practitioners, buyers and analysts. We support conference submissions such as Black Hat and DEF CON, including time to prepare and travel to present. Vulnerabilities you find go through responsible disclosure and get CVEs where they qualify. • Collaborate. Work with Alice's large research organization, which partners with leading hyperscalers and foundation model labs. Follow new papers, disclosures and exploits, and decide which ones matter for enterprises deploying agents. Success Looks Like 90 days in, you have published at least one research piece on enterprise agent risks. Its findings have shaped new protections in the Alice platform. Requirements • 4+ years in security research, offensive security, penetration testing or vulnerability research. • Hands-on experience with direct and indirect prompt injection, jailbreaks, data exfiltration and tool misuse against real systems. • Strong Python. You build your own tooling and test environments. • Working knowledge of how agents are built: tool calling, MCP, retrieval, memory and multi-agent orchestration, with hands-on use of at least one agent framework. • Familiarity with AI security frameworks (OWASP Top 10 for LLM Applications and for Agentic Applications, MITRE ATLAS) and with public agent safety and security benchmarks. • Experiment discipline: reproducible setups, controls, and enough runs to trust a result. • Clear writing and presentation: test results the product team can act on, and research that marketing can publish. • Fluent English, written and spoken. Nice to Have • Published research, CVEs, conference talks, or a bug bounty or CTF record in AI or application security. • Experience researching AI safety failures, such as harmful outputs or unsafe autonomous actions. • A background in adversarial machine learning. • Experience building or evaluating detection systems that use AI. • Experience working with product and engineering teams to turn research into shipped features. About Alice Alice is a trust, safety, and security company built for the AI era. We safeguard the communicative technologies people use to create, collaborate, and interact- whether with each other or with machines. In a world where AI has fundamentally changed the nature of risk, Alice provides end-to-end coverage across the entire AI lifecycle. We support frontier model labs, enterprises, and UGC platforms with a comprehensive suite of solutions: from model hardening evaluations and pre-deployment red-teaming to runtime guardrails and ongoing drift detection. Alice is widely considered a global leader in online safety and AI security. We have some of the most forward-thinking and passionate minds in the world working to safeguard over 3 billion users across the largest AI and tech platforms. If you're creative and driven to secure the future of AI, we want to hear from you!

Description Cybersecurity & Trust and Safety | RLGym We are looking for a Director of AI Research & Data Operations to lead and scale RLGym's research and data generation efforts, delivering high-quality training and evaluation data to frontier AI models at scale. This role combines research leadership, data science, and large-scale operational management. You will build and lead multidisciplinary teams of researchers, data scientists, domain experts, and operations specialists, transforming complex research challenges into scalable, high-quality data production systems. The ideal candidate brings experience managing large research and data operations, a strong understanding of modern AI and LLM development, and the ability to deliver high-quality datasets that advance frontier model capabilities, with a particular focus on cybersecurity and trust & safety. What you'll be doing • Lead and scale large AI research and data operations, managing multidisciplinary teams of researchers, data scientists, domain experts, and operational leaders. • Own the end-to-end generation and delivery of high-quality training and evaluation datasets for frontier AI models, ensuring scalability, consistency, and research value. • Define the research strategy, operational roadmap, and data generation priorities across cybersecurity, trust & safety, and emerging AI capabilities. • Build and optimize large-scale data production pipelines, combining human expertise, automated workflows, synthetic data generation, and AI-assisted research. • Establish rigorous data quality frameworks, including validation methodologies, quality assurance processes, benchmarking, and continuous improvement. • Lead research initiatives focused on generating realistic, challenging, and diverse datasets for LLMs, GenAI applications, and agentic AI systems. • Work closely with research, product, engineering, and data science teams to translate frontier model requirements into actionable research programs and scalable data deliverables. • Develop scalable systems for expert-driven data generation, evaluation, annotation, and human feedback, including workflows supporting supervised fine-tuning and reinforcement learning. • Define and track operational and research KPIs, balancing data quality, throughput, cost efficiency, and delivery timelines. • Build partnerships with external researchers, domain experts, and research organizations to expand data generation capabilities and domain expertise. • Drive innovation in data generation methodologies, evaluation benchmarks, and research infrastructure to continuously improve the quality and impact of RLGym's data. Requirements What we need to see • Proven experience leading and scaling large research, data science, AI/ML, or data operations teams. • Strong experience managing complex, high-volume data generation or research operations, with measurable quality and delivery outcomes. • Deep understanding of AI/ML development, LLMs, GenAI, and the role of training and evaluation data in improving model performance. • Experience designing and implementing data quality frameworks, evaluation methodologies, and scalable research workflows. • Ability to translate complex research objectives into structured execution plans and deliver results at significant scale. • Strong analytical and data-driven decision-making skills, with experience defining operational metrics and optimizing research processes. • Experience managing multidisciplinary teams and collaborating with research scientists, engineers, and domain experts. • Strong strategic leadership, operational execution, and cross-functional communication skills. • Familiarity with cybersecurity, AI security, or trust & safety challenges and their relevance to frontier AI model development. • 8+ years of relevant experience in AI/ML, data science, research leadership, large-scale data operations, or related technical fields. Ways to stand out • Experience delivering large-scale training or evaluation datasets to leading frontier AI labs. • Background in human feedback, RLHF, reinforcement learning environments, synthetic data generation, or expert-driven annotation programs. • Experience building data generation platforms, automated evaluation pipelines, or large-scale AI research infrastructure. • Familiarity with cybersecurity and trust & safety datasets, adversarial evaluations, or AI red-teaming methodologies. • Experience developing data quality measurement systems, including automated grading, expert calibration, and statistical quality control. About Alice Alice is a trust, safety, and security company built for the AI era. We safeguard the communicative technologies people use to create, collaborate, and interact- whether with each other or with machines. In a world where AI has fundamentally changed the nature of risk, Alice provides end-to-end coverage across the entire AI lifecycle. We support frontier model labs, enterprises, and UGC platforms with a comprehensive suite of solutions: from model hardening evaluations and pre-deployment red-teaming to runtime guardrails and ongoing drift detection. Alice is widely considered a global leader in online safety and AI security. We have some of the most forward-thinking and passionate minds in the world working to safeguard over 3 billion users across the largest AI and tech platforms. If you're creative and driven to secure the future of AI, we want to hear from you!

Description Alice.io (formerly known as ActiveFence) is a leading trust, safety, and security company. Just like 'Alice' herself, we go down the rabbit hole into the emerging world of AI and focus on safeguarding these technologies. In a world where AI has fundamentally changed the nature of risk, Alice offers coverage across the entire AI lifecycle. We're currently on the ground floor of an exciting new initiative: building an "Elite Collective" of the world's premier OSINT/WEBINT experts—high-stakes, project-based work for the "best of the best" researchers in the industry. Work is on-demand and project-dependent, scaling up and down based on the needs of the client. This is not a high-volume, repetitive role; it is an opportunity to be tapped for specific, high-impact interventions when your unique expertise is required. The most sophisticated technology challenges in the world are waiting down the rabbit hole. We're looking for the sharpest minds to help us secure the frontier. The invitation is open: Come join us at the tea party. About the Position As one of Alice's OSINT/WEBINT Researchers, you'll conduct in-depth open-source and web intelligence research to identify, analyze, and assess a wide range of online threats and harmful activities across platforms. Your work directly supports the safety of some of the world's largest digital platforms. We are seeking researchers with expertise in one or more of the following domains: • Child Safety - Detecting and analyzing child sexual abuse material (CSAM) and grooming indicators • Hate Speech & Extremism - Tracking radicalization trends, hate groups, and violent ideologies • Counterterrorism - Identifying terrorist propaganda and networks • Organized Crime - Investigating illicit trade, fraud, and trafficking operations • Platform Integrity & Manipulation - Uncovering coordinated inauthentic behavior, influence operations, and misinformation campaigns Key Responsibilities • Conduct end-to-end intelligence research projects across multiple abuse areas (hate speech, violent extremism, child safety, platform manipulation, organized crime, fraud, and disinformation) • Collect, analyze, and contextualize data from a variety of open and closed sources, including social media platforms, chat applications, gaming platforms, forums, and AI tools • Apply OSINT/WEBINT methodologies (search, dorking, verification, network mapping, and trend analysis) to identify indicators of online threats and harmful behavior • Prepare concise analytical reports and datasets, summarizing key findings, insights, and emerging risks • Stay up to date on global online threat trends and evolving tactics across different platforms • Collaborate with internal and external stakeholders (e.g., Delivery, Product, and Policy teams) to ensure timely and high-quality outputs Requirements • 2+ years of experience conducting online research or intelligence analysis (OSINT/WEBINT, investigations, or Trust & Safety) • Proven ability to manage and deliver research projects independently, from data collection to reporting • Fluent or native-level English (both written and spoken) • Strong analytical and writing skills, with the ability to synthesize large volumes of data into clear, actionable insights • Familiarity with online platforms and digital ecosystems, including social media, messaging, and content-sharing networks • Technical literacy: ability to work with spreadsheets, search operators, data collection tools, and AI-assisted workflows • Resilience to sensitive or disturbing content, including exposure to violent, extremist, or sexual materials Preferred Qualifications • Additional language skills • Academic or professional background in international relations, political science, criminology, communication, or related fields • Experience in one or more domains: Counterterrorism, Hate Speech, Child Safety, Disinformation, or Organized Crime Additional Requirements • Excellent organizational and multitasking abilities; able to manage multiple projects simultaneously • Proactive mindset, curiosity, and eagerness to learn about new digital ecosystems • Team-oriented, collaborative, and comfortable working in fast-paced, cross-functional environments • Capability to maintain professional boundaries and follow data sensitivity and privacy guidelines All applicants will be required to complete a screening exam and background check. About Alice Alice is a trust, safety, and security company built for the AI era. We safeguard the communicative technologies people use to create, collaborate, and interact- whether with each other or with machines. In a world where AI has fundamentally changed the nature of risk, Alice provides end-to-end coverage across the entire AI lifecycle. We support frontier model labs, enterprises, and UGC platforms with a comprehensive suite of solutions: from model hardening evaluations and pre-deployment red-teaming to runtime guardrails and ongoing drift detection. Alice is widely considered a global leader in online safety and AI security. We have some of the most forward-thinking and passionate minds in the world working to safeguard over 3 billion users across the largest AI and tech platforms. If you're creative and driven to secure the future of AI, we want to hear from you!

Description Alice is hiring a Senior Software Developer to lead the development of our internal malware research platform. This is a senior, hands-on role with end-to-end ownership of development and delivery. You'll be the technical authority — setting code-quality standards, making the architecture calls, and mentoring the developer team. What makes this role different is who you build for. Our users are our malware researchers, and they use the tool every day. Your job is to sit beside them, learn how they actually work, surface the heuristics and edge cases they carry in their heads, and build agentic tooling that compounds their productivity. The bar isn't "does it ship" — it's "do the researchers reach for it every day." Success is measured in researcher adoption and time saved, not features merged. Agentic workflows are core to how we build. You should be fluent using them and confident designing systems where agents run in production — with clear judgment about where an agent earns its keep versus where deterministic code or a human-in-the-loop is the right call. What You'll Do Lead development and delivery • Own technical execution end-to-end: implementation, code review, and release. • Translate research workflows and feature requests into well-scoped tasks with realistic, risk-aware estimates the team can plan against. • Manage day-to-day execution: unblock people, sequence work, catch problems early. • Set and defend the technical bar: review rigor, testing discipline, documentation, architectural consistency. Partner with the researchers — and amplify them • Embed with malware researchers to understand their workflow and capture the tacit knowledge and edge cases no spec ever wrote down. • Translate that knowledge into reliable agentic tooling — and know when an agent is confidently wrong before it ever reaches a researcher. • Spend roughly 5–10% of your time doing actual malware research (with structured onboarding) to stay close to how the tool is used. • Be willing to tell a researcher when a proposed workflow won't automate well — and explain why. Be the technical authority and mentor • Make the hard architecture and design trade-off calls. • Mentor through code review, pairing, and design discussions. Raise the level of everyone around you. • Dive deep on the critical, difficult features and bug fixes yourself. • Design agentic workflows into the architecture from the start, and build the evaluations and guardrails that keep them trustworthy. Requirements Must-have • 5+ years of software development experience, with a track record of delivering products to production — not just prototypes or POCs. • Strong Python, including async (asyncio), modern typing, and a disciplined testing approach (pytest). • Hands-on Playwright experience in production — not one-off scripts. • Production experience with agentic workflows: building, deploying, and operating LLM-powered systems that plan, call tools, and execute multi-step tasks — using a modern agent framework (e.g., LangGraph, the Anthropic Claude Agent SDK, the OpenAI Agents SDK, or DSPy). • Experience building evaluations and guardrails to measure agent quality and catch regressions before they reach a user (e.g., MLflow GenAI evaluation & tracing, LangSmith, or Braintrust). • Proven experience leading development efforts: estimation, task breakdown, code review, and mentoring. • Experience building tools used internally by expert users (vs. external end-user products), or a clear instinct for the difference. Nice to have • Background in cybersecurity, malware research, threat intelligence, or an adjacent security domain. • Experience with reverse-engineering tools, sandboxes, or malware-analysis pipelines. • RAG and retrieval pipelines (indexing, reranking, grounding) and a vector store (e.g., pgvector). • Cloud-native infrastructure (AWS, Kubernetes), containers (Docker), CI/CD (GitHub Actions), and observability stacks (OpenTelemetry, Grafana / Coralogix or equivalent). About Alice Alice is a trust, safety, and security company built for the AI era. We safeguard the communicative technologies people use to create, collaborate, and interact- whether with each other or with machines. In a world where AI has fundamentally changed the nature of risk, Alice provides end-to-end coverage across the entire AI lifecycle. We support frontier model labs, enterprises, and UGC platforms with a comprehensive suite of solutions: from model hardening evaluations and pre-deployment red-teaming to runtime guardrails and ongoing drift detection. Alice is widely considered a global leader in online safety and AI security. We have some of the most forward-thinking and passionate minds in the world working to safeguard over 3 billion users across the largest AI and tech platforms. If you're creative and driven to secure the future of AI, we want to hear from you!