Twine Security

Twine builds AI Digital Employees who help cyber teams close the execution gap. Our first AI Digital Employee, Alex, learns, understands and takes away the burden of Identity and Access Management (IAM) tasks - proactively completing the organization's cyber objectives. About the role: You'll design, build, and ship the AI systems behind Alex: production agents that reason over customer identity data, call real tools, and complete IAM tasks end to end. Starting from a cybersecurity need, you'll frame the technical problem, choose an approach, and own the solution through production: architecture, implementation, evaluation, deployment, and iteration on real customer behavior. You'll build on Twine's shared agent infrastructure and extend it: new tools and integrations, workflow orchestration, context and memory management, evaluation harnesses, and the guardrails that keep an autonomous agent safe inside a customer's environment. This is a hands-on engineering role, not a research position. The goal is not to prove that an idea can work; it is to make it useful, reliable, and observable for customers in production. Responsibilities Design, implement, and ship AI-powered features for complex cybersecurity workflows, from prototype to production. Build the systems that make agents work in practice: tool integrations, planning and orchestration logic, context management, structured outputs, and recovery from failures. Choose the right technical approach for each problem, combining models, deterministic logic, data, and conventional software where appropriate. Define quality for each use case and build the evaluation pipelines that measure correctness, task completion, consistency, safety, latency, and cost, and wire them into CI and release. Debug agent behavior in production: trace failures to their root cause in the prompt, tool, data, or architecture, and fix it. Own the reliability, observability, and cost of the agent systems you build. Collaborate with cybersecurity experts, product, and platform engineers throughout development. Requirements Excellent software engineering skills and substantial production experience with Python. Experience shipping and operating backend systems in production: APIs, async processing, data pipelines, testing, and observability. Hands-on experience building applications on modern language models: tool use, structured generation, retrieval, prompt and context management, and evaluation. Sound judgment about when to use an AI technique and when a deterministic approach is more effective. Comfort owning a problem end to end, from an ambiguous requirement to a system running reliably in production. Nice to have Building autonomous or long-running agents that interact with real systems. Building evaluation pipelines, simulations, or benchmarks for model behavior. Experience in cybersecurity, identity, security operations, or enterprise automation. Experience with agent frameworks, MCP, or LLM observability and tracing tools. Intertwine your future with ours Applying for AI Engineer. Send us your details and CV - we read every one.

Twine builds AI Digital Employees who help cyber teams close the execution gap. The first AI Digital Employee, Alex, learns, understands and takes away the burden of Identity and Access Management (IAM) tasks - proactively completing the organization's cyber objectives. This role seeks an experienced Backend Engineer with 5+ years of experience to help build core infrastructure for Twine's agentic AI system. This is not another workflow tool: we are building something new, in a category that does not really exist yet. Responsibilities Build production backend services in Python that power Twine's agentic AI platform. Design and implement AI-agent orchestration, tool-calling infrastructure, workflow execution, guardrails, and evaluation loops. Integrate with enterprise applications, identity providers, SaaS tools, and customer data sources so agents can understand context and execute tasks safely. Build systems that ingest, model, and reason over organizational processes, permissions, policies, and internal knowledge. Solve scale and reliability challenges for large enterprise environments with tens of thousands of identities. Collaborate closely with product, AI, and customer-facing teams to turn ambiguous business processes into reliable automated experiences. Own reliability, observability, performance, and security for production systems. Requirements 5+ years of professional backend engineering experience. Strong expertise in Python and production service development. Experience building complex, production-grade backend systems such as APIs, data pipelines, distributed systems, or workflow engines. Hands-on experience or strong practical familiarity with LLMs, agentic AI, tool calling, RAG, workflow orchestration, or AI infrastructure. Ability to design systems that use AI safely: validation, guardrails, evaluation, observability, and controlled execution. Solid understanding of databases, data modeling, and API design. Comfort working with ambiguous product requirements and turning them into robust technical designs. Excitement about building a new category and solving problems that do not have off-the-shelf answers. Nice to have Experience with identity, security, governance, permissions, or enterprise SaaS integrations. Experience with LLM evaluation, tracing, observability, or production AI systems. Experience building systems that automate complex operational workflows end-to-end.

Twine builds AI Digital Employees who help cyber teams close the execution gap. The first AI Digital Employee, Alex, learns, understands and takes away the burden of Identity and Access Management (IAM) tasks - proactively completing the organization's cyber objectives. We are looking for a Software Engineer - Customer Solutions to help customers successfully integrate, configure, and deploy our platform. You will work directly with customers to understand their technical requirements, build integrations, and troubleshoot issues across APIs, data, authentication, and enterprise systems. This role combines hands-on engineering with customer interaction, requiring strong technical fundamentals, curiosity, clear communication, and a practical approach to solving real-world problems. Responsibilities Work directly with customers to understand their technical workflows and integration needs Build and configure integrations between our platform and customer systems Develop backend services, scripts, APIs, data transformations, and automation workflows Investigate technical issues involving APIs, databases, authentication, customer data, and infrastructure Participate in customer implementation meetings and help translate business requirements into technical tasks Test, deploy, monitor, and support customer-facing solutions Document integrations, troubleshooting steps, and implementation decisions Work closely with senior engineers and product teams to turn customer-specific needs into reusable capabilities Gradually take ownership of increasingly complex customer projects Requirements Bachelor's degree in Computer Science or a related technical field 1-3 years of software engineering, implementation engineering, technical consulting, or equivalent hands-on experience Strong programming fundamentals, preferably using Python, or another backend language Apply an AI-first approach to problem solving, leveraging AI tools to accelerate development, debugging, and solution design while maintaining strong judgment Basic experience building or consuming REST APIs Working knowledge of SQL and relational databases Ability to debug technical problems methodically Strong communication skills and comfort speaking with technical customers Ability to learn unfamiliar systems quickly Organized, dependable, and comfortable managing multiple tasks Willingness to work across coding, customer communication, testing, deployment, and support Nice to have Experience with enterprise software integrations Experience with cloud platforms, Docker, CI/CD, or production monitoring Experience in cybersecurity, identity, IT systems, or enterprise SaaS Previous customer-facing engineering, support engineering, or implementation experience