You will own the design and delivery of the platform services behind that work: the control planes, the policy and enforcement paths, and the APIs other teams build on
Responsibilities
Design and build the platform services at the core of the product: control planes, policy and enforcement paths, and the APIs other engineers build on
Own services end to end, from architecture and implementation through deployment and production operation
Solve the distributed systems problems that come with running a single platform across on-prem, public cloud, and SaaS: consistency, partial failure, rollout and upgrade, and scale
Build the paths that AI workloads run through, including inference and serving, agent runtimes, and the data that moves between them
Make the platform's security guarantees real in the code: identity and access, workload isolation, secrets handling, and secure-by-default patterns
Translate hybrid and sovereign cloud requirements such as data residency, isolation, encryption, and access control into concrete, implementable designs
Raise the technical quality of the team through design reviews, code review, and pairing
Requirements
BSc in Computer Science, or equivalent practical experience
5+ years building server-side software, including systems you designed, shipped, and operated in production
Depth in complex distributed systems: services that span multiple environments, and the problems that come with them — consistency, partial failure, upgrade and rollout, scale, and debugging things that only break in production
Strong in at least one modern backend language (Java, Go, Python, or similar), with solid API and data modeling instincts
Working knowledge of at least one major cloud (AWS, Azure, or GCP), and how AI workloads get deployed on it
Using AI coding agents like Claude or Cursor in your day-to-day work.
Advantage
Hands-on experience building with AI agents: LLM/SLM-based agents, orchestration frameworks, tool use, MCP, prompt and context engineering, retrieval - and a sense of how to evaluate agent behaviors.
Experience deploying and operating AI workloads: inference and serving, GPU scheduling, model and data pipelines.
Experience in AI security: how AI systems get attacked (prompt and tool injection, data-pipeline abuse, agent failure modes) and how to defend them.
Work in sovereign or regulated environments, where data residency and isolation matter.
Familiarity with security or AI governance frameworks such as ISO/IEC 42001, the NIST AI Risk Management Framework, or the EU AI Act. Policy-as-code and compliance automation count here too.
M.Sc. or Ph.D. in Computer Science, Cybersecurity, or Machine Learning.
What Lenovo Can Offer You
Opportunities for career advancement and personal growth
Access to a diverse range of training programs to sharpen your skills
Performance-based rewards that celebrate your achievements
Enjoy the best of both worlds with our hybrid setup: 3 days connecting with the team in the office and 2 days working from the comfort of your home
Please note that the office is located at 121 Menachem Begin Road, Tel Aviv, 61st floor, in the POINT office complex. As per our office policy, you will be required to visit the site at least 3 times a week.
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We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race, color, sex, age, religion, sexual orientation, gender identity, national origin, status as a veteran, and basis of disability or any federal, state, or local protected class.
Additional Locations
Israel
Israel
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