Tech Lead jobs in Tel Aviv-Yafo

About PointFive PointFive finds the cost buried inside enterprise infrastructure, from the cloud to coding agents. We pioneered DeepWaste across cloud and data platforms, and we are now doing the same for AI token spend with TokenShift. Fanatics, H&M, Hertz, Nubank, Citizens Bank and other Fortune 500 companies use PointFive to see and cut what their infrastructure and AI actually cost. We have raised $96 million, most recently a $60 million Series B led by Accel. Engineering sits in Tel Aviv and our go-to-market team is focused on North America. PointFive Labs, our research arm, publishes original work on how infrastructure and AI actually get paid for. CRN named us one of the 10 hottest cloud computing startups of 2026, Forbes Israel put us on its Next Billion Dollar Startups list, and Redpoint selected us for its InfraRed 100, its ranking of the private companies shaping the future of cloud infrastructure. About the Role We're looking for an exceptional, hands-on leader-engineer to join our core engineering team as a true force multiplier and technological anchor for the company. You'll have the flexibility to drive high-impact initiatives from conception to production, own complex technical and AI domains end-to-end, or guide and level up a focused delivery team — operating with a high degree of autonomy in an ambiguous, fast-moving environment. What You'll Do • Drive strategic initiatives: lead complex technical projects, AI feature developments, and core architectural components with an ownership mindset. • Architect for AI & data at scale: design robust, scalable infrastructure and pipelines capable of handling massive volumes of cloud infrastructure data. • Bridge product, AI & tech: collaborate closely with Product Managers and data specialists to translate business roadmaps into high-performance technical systems. • Promote engineering excellence: establish development guidelines, lead design and architecture reviews, and raise the bar for code quality across teams. • Mentor & guide: act as a technical mentor to fellow engineers through hands-on collaboration, deep code reviews, and architectural consultation. What We're Looking For Must-have • 8+ years of experience in backend software engineering, with a proven track record designing, building, and operating large-scale cloud production systems. • Strong coding fundamentals in backend technologies such as Go, Python, Java, etc. • Experience leveraging AI coding agents (e.g., Claude Code) and implementing AI-oriented workflows to enhance team productivity and code quality. • Production-grade experience with AWS, containerization (Kubernetes/Docker), microservices, and distributed databases/data warehouses (e.g., PostgreSQL, Snowflake). • Practical experience working with large data volumes, data pipelines, or integrating AI/LLM technologies into production environments. • Demonstrated experience leading technical workflows, driving complex cross-team initiatives, or acting as a full-lifecycle domain owner. • A true independent operator who thrives in fast-paced environments and solves problems end to end. • Ability to build technical consensus, inspire peers, and drive alignment across stakeholders. Our Tech Stack Go, Python, Java, AWS, Kubernetes, Docker, PostgreSQL, Snowflake Why PointFive • Founders with a track record — Built and sold IntSights to Rapid7. Backed by top-tier investors with deep conviction in this category. • Category-defining product — DeepWaste detection and agentic remediation with clear, measurable ROI for both engineering and finance teams. • Early-stage leverage — Your work directly shapes the product, the culture, and the go-to-market playbook. • Step into a leadership track on a lean, senior engineering team — set direction for architecture and mentorship from day one.

Scope: Hands-on technical lead, no direct reports — influence across Copilot & AI, Pipeline, and Experience About Miggo We're Miggo — a cybersecurity startup on a mission to stop app-layer breaches before they happen. Founded in 2023 and backed by top-tier cyber VCs, we're building the world's first Application Detection & Response (ADR) platform. Why? Because 80% of cyber attacks target the app layer, and current tools just don't cut it. Miggo brings visibility into how apps actually behave at runtime, spotting risky flows and shutting down threats in real time. We're closing the patch gap: showing security teams what's reachable, what's exploitable, and what's being attacked right now — and delivering targeted mitigations when a patch isn't ready. At Miggo, we live by four core values: • We make it customer-focused — user needs are our north star. • We make it happen — driven by execution and a can-do mindset. • We make it better — always pushing boundaries and learning fast. • We make it together — one team, thriving on collaboration and diverse perspectives. About the Role Miggo already runs agents in production. Our WAF Copilot takes a freshly disclosed CVE and turns it into a validated, provider-specific WAF rule — a state-driven agent graph that researches the vulnerability, maps the attack surface, composes the rule, then attacks its own output with an independent bypass judge and a false-positive prober before a human is ever offered a deploy. When a weakness survives, the system downgrades its own recommendation and records what it could not prove. That last part is the thesis of this role. An agent that touches production security must prove it works and declare what it couldn't prove. The security industry is about to be flooded with agentic claims nobody can verify. We intend to be the company that made verification legible — and that starts with holding our own agents to a standard we're willing to publish. We're looking for an AI Tech Lead to own that standard across three surfaces: • The platform - Today each agent flow is close to a bespoke implementation. You'll turn our hard-won patterns into shared components, conventions, and infrastructure so the next agent is a week of work rather than a quarter — with evaluation, observability, and cost control built in rather than bolted on. • Enablement - Miggo's advantage compounds only if the whole company is AI-fluent, not just R&D. You'll raise that fluency everywhere — engineering, research, product, GTM — through tooling, patterns, and teaching. • The voice - You'll publish the methodology: how we benchmark agentic security output, how we model residual risk, what we learned failing. This is a category-defining position and we want it argued in public. This is a hands-on lead role with no direct reports. Your authority comes from the quality of what you build and how clearly you explain it. What You'll Do • Define and build Miggo's agent framework — shared components, orchestration patterns, tool interfaces, and conventions that make "how do I build an agent here" a five-minute answer. • Make evaluation a gate, not an afterthought: trajectory testing, golden datasets, offline replay, and per-dimension scoring that runs in CI. Land the release benchmark so promote / hold / rollback is a number, not a vibe. • Own agent observability end to end — the execution graph, tool invocations, intermediate reasoning, latency per step, and quality drift — including the external Temporal-orchestrated flows that are hardest to introspect today. • Own the economics: provider abstraction, model routing by task complexity, small-model substitution where it holds, cost attribution per flow. Thousands of CVEs through a labeling agent is a budget line, not a detail. • Drive latency and determinism in our production agent flows — tighter loops, early stopping, deterministic state machines over prose-in-prompt orchestration. • Raise the company's AI fluency. Build the internal tooling, skills, and playbooks that let every team — not just R&D — work AI-natively, and teach the judgment for when not to. • Partner with security research, product, and engineering leadership so agent capability and product roadmap actually converge. What You'll Have • You've shipped agentic systems to production — real orchestration, tool use, structured outputs, and the failure modes that only appear at scale. Not "I've called an LLM API." • You've built the evaluation discipline, not just consumed it: trajectory tests, golden datasets, regression gates, offline replay. "It seems better" is not a metric, and you have opinions about what is. • Deep backend and distributed-systems engineering. Strong Python, and comfort with workflow orchestration (Temporal or equivalent), streaming, and cloud-native infrastructure. Agent platforms are systems problems wearing an AI hat. • Fluency across the modern agent stack — LangChain/LangGraph-style frameworks, multi-provider routing, structured output contracts, prompt and context engineering — with the judgment to know which parts are load-bearing and which are fashion. • Security literacy. Enough to reason about whether an agent's security output can be trusted, and to argue with researchers on the merits. You don't need to be a vulnerability researcher. • Influence without authority. You'll change how three teams work with no one reporting to you. Show us where you've done that. • Advantage: experience with AI/LLM security — red-teaming agents, prompt injection, or agentic attack patterns. • Advantage: background in cybersecurity, detection engineering, or WAF/mitigation systems. • Advantage: you've driven AI adoption across a whole company, not only an engineering org. We deliberately don't list a years-of-experience bar. Agent engineering is a few years old as a discipline — we care what you've shipped and what you learned when it broke. Why Miggo? Most "AI lead" roles are a greenfield promise. This one isn't: there are real agents in production, real customers behind them, and a genuinely hard standard already half-built. You'll get the leverage of setting how an entire company builds with AI, the autonomy of a hands-on lead with no layers to negotiate, and a platform to argue the methodology in public while the category is still being defined. We're small enough for your conventions to become how Miggo works — and bold enough to publish them. <!-- notionvc: ed497ce1-f06b-42c5-be56-ef1286b4799f -->

Description At Sunbit, we're building financial technology that puts people first. By combining intelligent decisioning with a personalized, transparent approach, we help consumers access the payment options that are right for them while empowering merchants to build stronger customer relationships. Engineering is at the heart of how we make that happen. We build scalable distributed systems, cloud-native services, intelligent data platforms, and AI-powered solutions that enable real-time financial decisions at scale. By leveraging modern engineering practices and integrating AI into both our products and development workflows, we solve complex technical challenges, accelerate innovation, and continuously improve the way we build software. Every service, model, and architectural decision we make directly impacts our products, our customers, and the future of financial technology. What You’ll Do: Our engineering squads are responsible for critical domains and products that power our platform and support our users' ongoing relationship with us. The teams develop scalable web platforms, backend services, and applications, and are comprised of skilled engineers across the stack (backend, frontend, and data). As a Squad Lead, you will be responsible for the team's technical leadership, domain design, and day-to-day execution. You will collaborate closely with product managers and business stakeholders to define priorities and deliver impactful solutions that align with key business goals. We are looking for someone who can drive end-to-end ownership, balance business needs with strong engineering practices, and help shape the direction of our products. Responsibilities: • Among your key responsibilities, you will lead a highly skilled team that architects and builds scalable systems that serve our customers and partners. • Technical Architecture - Lead the technical architecture and system design for core products and services within your domain. • Team Leadership - Guide a multidisciplinary squad of frontend, backend, and data engineers through implementation, delivery, and iteration. • Stakeholder Collaboration - Work closely with product managers and business stakeholders to translate requirements into scalable technical solutions. • Strategic Alignment - Ensure development aligns with business objectives, long-term system health, and Sunbit’s engineering standards. • Quality - Conduct and lead design reviews, code reviews, and performance optimization efforts. • Culture Building - Drive a culture of technical excellence, ownership, and continuous improvement. • Operational Excellence - Oversee system reliability, monitoring, and incident response within your domain. Requirements • 2+ years of leadership experience, guiding engineering teams and making architectural decisions • 8+ years of software engineering experience, with a strong focus on scalable architecture and system design • Proficiency in modern system architecture with large-scale and high performance. • Impact driven - use data to make sure every task moves the needle and utilize your resources to maximize the team's impact. • Team player with strong communication skills and someone who thrives working in a fast-paced environment. • Creative, solution-oriented, and able to maintain a ‘can do’ attitude, with the ability to work efficiently under pressure and uncertainty. Adapt quickly to changing business needs. • Familiarity with microservices architecture and distributed systems. • B.Sc. in Computer Science or equivalent. • Fluent in English. • Experience with AI tools and a strong interest in continuously exploring and applying them in everyday work are highly valued. Preferred Experience: • Experience with software development in Kotlin or Java. • Experience with Frontend technologies. • Experience with mobile technologies. • Leading a multidisciplinary team. • Familiarity with microservices architecture and distributed systems. • Solid understanding of AWS or similar cloud platforms. • Expertise in the Spring Framework. • Proficient in both relational (e.g., MySQL) and non-relational databases (e.g., MongoDB). • Familiarity with message queue technologies such as Kafka, SQS, RabbitMQ, or similar. Recruitment Fraud Disclaimer We’ve been made aware of fraudsters impersonating Sunbit employees during the hiring process. Please note that all official communication will come from an @sunbit.com email address, through our applicant tracking platform @sunbit.comeet-notifications.com or directly via LinkedIn. We will never ask for your age, Social Security number, bank account details, payment of any kind, or other unrelated personal information during the application process. Our hiring process always includes interviews, either by phone, zoom, or in person, before any offer is made. If something feels suspicious, please contact us at [email protected] to confirm. We ask that you contact [email protected] only about potential instances of fraud. [email protected] does not reach our recruiting team directly. Your application directly through the posting is the best way to ensure that your candidacy is reviewed by our team. Due to the volume of applications, we will not respond to nor forward emails about your candidacy that are sent to [email protected] directly, and your email about your application will be deleted from our systems.

Description Fetcherr builds responsible AI that transforms market complexity into measurable profit growth. At the core of the company is the Market Model, a proprietary AI-powered model delivering accurate, granular demand predictions with 96% forecast accuracy and real-time decision intelligence for commercial teams. Built on a glass-box architecture, it uses market data, not personal data, with full transparency into logic and outcomes. First deployed in global aviation, the technology is industry-agnostic and scales across volatile markets. Fetcherr delivers a consistent average profit uplift of 7%, with corporate partners including Delta, Virgin Atlantic, WestJet, Viva, and Azul. The Large Market Modeling (LMM) team is the engine underneath Fetcherr's pricing intelligence. We're the ones who actually build and train the models — taking a chaotic world of market signals, customer behavior, and competitive dynamics and turning them into reliable, production-ready demand models. Other teams at Fetcherr work with the models; we're the ones who bring them to life. Think of us as the team that teaches Fetcherr's AI how people buy — so it can always recommend the right price at the right moment. We are looking for an Engineering Team Lead to lead the MLOps efforts - drive the development of an internal machine learning platform for a group of ML teams. This is a hands-on leadership role: you will guide a small team of MLOps engineers that builds the automation and infrastructure powering our research (R&D) workflows and runs our pipelines to production. You will take ownership of end-to-end initiatives and drive the team toward critical infrastructure and model-lifecycle milestones, while staying close enough to the code to set technical direction and raise the bar by example. You will be responsible for building and maintaining the models and data pipelines behind our data science workflows, ensuring the accuracy, consistency, and efficiency of the data used for training and inference, working across structured and unstructured data from many sources on a large-scale, distributed platform. Responsibilities: • Lead, mentor, and grow a team of MLOps engineers, owning delivery and technical quality. • Take end-to-end ownership of infrastructure and pipeline initiatives across the LMM group, from design through production. • Stay hands-on: contribute to design and code, review work, and set engineering standards. • Drive the team through critical milestones in ML model-lifecycle and infrastructure ownership. • Partner with R&D and other stakeholders to translate research needs into robust, scalable systems. • Help evolve the platform, including our ongoing migration from Dask to Ray. Requirements • BSc or Master's degree in Computer Science, Mathematics, or Engineering. • At least 5 years of commercial experience in Python. • At least 3 years of hands-on commercial MLOps experience in production (not side projects). • Experience managing or leading a team of engineers, with ownership of both people and delivery. • Hands-on experience owning the ML model lifecycle (training, deployment, monitoring, retraining). • Experience with pipeline orchestrators such as Dagster or Airflow. • Experience with a major cloud provider such as GCP, AWS, or Azure. • Experience with distributed computing systems. • Experience with Docker. • Experience with Kubernetes. • Commercial experience writing and maintaining scalable ML systems. • Fluent in English, both written and spoken. Nice to have: • Experience with Dagster (Advantage). • Experience with Dask or Ray (Advantage). • Experience with Spark, including implementing distributed algorithms in Python (Advantage). • Experience with traditional predictive, forecasting, or pricing-optimization ML systems (Advantage). • Experience in aviation, demand forecasting, or price optimization (Advantage). • Good understanding of data structures and algorithms (Advantage).

We Are Teva We’re Teva, a leading innovative biopharmaceutical company, enabled by a world-class generics business. Whether it’s innovating in the fields of neuroscience and immunology or delivering high-quality medicine worldwide, we’re dedicated to addressing patients’ needs now and in the future. Here, you will be part of a high-performing, inclusive culture that values fresh thinking and collaboration. You'll have the room to grow, the flexibility to balance life with work, and the opportunity to better health worldwide, together. Our Team, Your Impact DADAI (Data, Analytics, Digital & AI Delivery) is building a next generation enterprise delivery engine that turns the company’s biggest opportunities into measurable outcomes using data products, digital automation and applied AI. The ambition is to combine startup pace with enterprise discipline: product thinking, predictable delivery at scale, strong engineering standards, and clear architecture, security and quality gates that enable speed without compromising control. DADAI has been shaped as an enterprise “factory”, 200+ engineers, designed to absorb significant demand across multiple global domains, industrializing the path from idea to production and continuous improvement while scaling through strategic partners and still preserving internal knowledge and ownership. This is a rare opportunity to join a new leadership organization and to help set how the Teva will use data, analytics and AI to modernize decision making, automate critical processes, and accelerate innovation across core functions and value chains. Location This role can be based in Israel (Tel Aviv), Germany (Ulm), India (Bangalore), Poland (Warsaw) or United Kingdom (Harlow). The Role The AI Technical Lead owns the technical delivery of production-grade AI systems across enterprise digital, data, and analytics environments. This role sets engineering direction and provides strong hands-on leadership to design, build, deploy, and operate enterprise AI capabilities on a Microsoft-first stack, including agentic systems, generative AI applications, AI-enabled automation, and ML-powered platforms, ensuring consistent standards, quality, governance, security, and reliable global operations. Partners with enterprise architecture, security, privacy, legal, and central AI/data governance teams to enable delivery teams (internal and external partners) to build scalable, compliant, and auditable AI solutions across regions, cloud environments, and delivery models How You’ll Spend Your Day • Accountable for all AI engineering activities with in the DADAI delivery factory. • Lead the design, build, and operation of enterprise AI solutions on a Microsoft-first stack, including Azure OpenAI, Azure AI Foundry, Copilot Studio, Semantic Kernel, and Azure services. • Remain highly hands-on: review architecture and code, build proofs of concept, troubleshoot complex issues, and guide implementation teams through production hardening. • Define and enforce engineering standards for AI delivery, including evaluation, monitoring, release controls, security, privacy, and Responsible AI practices in regulated environments. • Work across architects, platform teams, security, and delivery stakeholders to ensure AI solutions are scalable, supportable, compliant, and aligned to business needs. Your Skills and Experience • 7+ years of proven experience leading and developing large (20+) engineering teams, including direct people management responsibilities, coaching, performance management, career development, and hiring in a complex enterprise environment. • 10+ years in software engineering, including senior hands-on design and delivery of applications and API in a modern Microsoft cloud environment. • 2+ delivering complex enterprise production GenAI and agentic solutions on Microsoft technologies such as Azure OpenAI, Azure AI Foundry, Copilot Studio, RAG, and evaluation workflows. • Strong Azure engineering background, including Azure Functions, App Services, AKS, API Management, Entra, CI/CD, monitoring, and production support. • 10+ years Hands-on technical leadership with proven ability to build POCs, MVPs and production applications, review code and architecture, troubleshoot production issues, and lead implementation teams by example. • 5+ years of experience working in enterprise or regulated environments with strong security, privacy, governance, and Responsible AI controls. • Strong communication and stakeholder management skills across architecture, security, delivery, and business teams. • BSc/BA in Computer Science, Software Engineering, Information Systems, or equivalent experience; relevant Azure or AI certifications are a plus. Key Skills • Hands-on builder and technical leader who can design, prototype, review, and unblock complex AI implementations. • Strong problem-solving across prompts, models, retrieval, orchestration, runtime behavior, performance, and cost. • Ability to translate business needs into practical technical solutions, delivery plans, and engineering trade-offs. • Practical understanding of AI SDLC, evaluation, monitoring, rollback, and operational readiness for production systems. • Clear communication and strong collaboration in cross-functional, global delivery environments. Core Technology Stack • AI platforms: Azure OpenAI, Azure AI Foundry, Copilot Studio, Semantic Kernel, Prompt Flow • Azure engineering: Azure Functions, App Services, AKS, API Management, Logic Apps, Event Grid, Service Bus • Engineering and SDLC: Azure DevOps, GitHub Enterprise, Azure Machine Learning, CI/CD, evaluation pipelines, observability • Security and governance: Microsoft Entra, Purview, Key Vault, Defender, Azure Policy • Data and analytics: Azure AI Search, Microsoft Fabric, Azure Data Factory, Power BI, SQL How We’ll Take Care of You At Teva, better health starts from within, and that includes you. From day one, you’ll be supported with benefits designed to help you thrive in and out of work. This includes generous annual leave, reward plans, flexible working schedules (dependent on role), access to tailored health support, and meaningful ways to give back to the community.  When it comes to your career, you’ll be encouraged to explore, evolve, and shape your path. Twist, our one-stop shop for career development platform, gives you access to a wide range of possibilities, from learning programs and short-term projects to opportunities for internal growth. Here, you’ll be part of a culture that empowers you to reach your goals and prioritize your wellbeing every step of the way.  Already Working @Teva? Make sure to apply through our internal career site on Twist—your one-stop shop for career development Teva’s Equal Employment Opportunity Commitment Teva Pharmaceuticals is committed to equal opportunity in employment. It is Teva's global policy that equal employment opportunity be provided without regard to age, race, creed, color, religion, sex, disability, pregnancy, medical condition, sexual orientation, gender identity or expression, ancestry, veteran status, national or ethnic origin or any other legally recognized status entitled to protection under applicable laws. We are committed to a diverse and inclusive workplace for all. If you are contacted for a job opportunity, please advise us of any accommodations needed to support you throughout the recruitment and selection process. All accommodation information provided will be treated as confidential and used only for the purpose of providing an accessible candidate experience.