Tech Lead, Software Engineering - Cloud Team

Lenovo's Enterprise AI team is hiring a Software Engineering Tech Lead to design and implement the security services that protect Enterprise AI across modern hybrid environments — securing AI workloads and agents deployed across on-prem datacenters, public cloud, and SaaS. Our current focus is AI sovereignty and governance in Lenovo hybrid cloud.

You will own the architecture and delivery of the platform services behind that work, set the technical direction for the team, raise the engineering bar, and mentor the engineers who build alongside you.

Job Responsibilities:

• Set the technical direction and own the architecture of the platform: control planes, policy and enforcement paths, and the APIs other teams build on.
• Lead design and delivery across the team: turn the roadmap into a technical plan, make the key trade-off calls, and keep execution on track.
• Stay hands-on: design, write, and review code for the most critical and complex parts of the system.
• Own the distributed systems challenges of running a single platform across on-prem, public cloud, and SaaS: consistency, partial failure, rollout and upgrade, and scale.
• Define how security is built into the platform: 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 architecture the team can implement.
• Work with product, research, and partner teams across Lenovo to align on requirements, interfaces, and priorities.
• Mentor engineers and raise the engineering bar through design reviews, code review, and pairing, and help hire and grow the team.

Requirements:

• BSc in Computer Science, or equivalent practical experience.
• 10+ years building server-side software, including systems you designed, shipped, and operated in production.
• Proven experience as a tech lead or architect: owning the design of systems other engineers built, and leading technical decisions across a team.
• 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.
• Clear technical communication: you can write a design doc, defend a trade-off, and bring engineers and stakeholders to a decision.
• Using AI coding agents like Claude or Cursor in your day-to-day work, with a view on how to make a whole team effective with them.

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 behavior.
• 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.

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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