AI Engineer - Agentic Systems in London

This role is based at Imperial College London . Applicants must be located in London, as the position requires on-site work at least three days per week under our 3:2 hybrid policy.
The Lenovo AI Technology Center (LATC)—Lenovo’s global AI Center of Excellence—is driving our transformation into an AI-first organization. We are assembling a world‑class team of researchers, engineers, and innovators to position Lenovo and its customers at the forefront of the generational shift toward AI. Lenovo is one of the world’s leading computing companies, delivering products across the entire technology spectrum, spanning wearables, smartphones (Motorola), laptops (ThinkPad, Yoga), PCs, workstations, servers, and services/solutions. This unmatched breadth gives us a unique canvas for AI innovation, including the ability to rapidly deploy cutting‑edge foundation models and to enable flexible, hybrid‑cloud, and agentic computing across our full product portfolio. To this end, we are building the next wave of AI core technologies and platforms that leverage and evolve with the fast‑moving AI ecosystem, including novel model and agentic orchestration & collaboration across mobile, edge, and cloud resources.
This space is evolving fast and so are we. If you’re ready to shape AI at a truly global scale, with products that touch every corner of life and work, there’s no better time to join us.
Lenovo is seeking a highly motivated Agentic Systems & Orchestration AI Engineer to contribute to the design, development, and exploration of our next‑generation AI systems. You will design and implement agentic AI systems: multi‑step agents, planners, tool‑using models, and orchestration layers that coordinate models, tools, and data. Your work turns LLMs from “text in/text out” engines into systems that can act, reason, and interact reliably. This is an exciting opportunity to gain hands‑on experience with cutting‑edge AI systems while collaborating with experienced engineers, researchers, and product teams to help advance Lenovo’s Hybrid AI vision and make Smarter Technology for All.
Responsibilities
Design and implement agents
Build agents that can plan tasks, call tools/APIs, decompose problems, and iterate based on feedback and intermediate results.
Orchestration & routing
Develop orchestration services that coordinate multiple models, agents, and tools (e.g., planners, executors, critics, evaluators), including policy logic and routing decisions.
Tooling & integration
Integrate agents with internal and external tools: APIs, databases, retrieval systems, transactional systems, and product features. Handle auth, error cases, and safety constraints.
Work closely with context management to maintain agent state across steps and sessions, including working memory, scratchpads, and long‑running workflows.
Reliability, safety & guardrails
Implement checks, constraints, and fallback policies so agents behave predictably and safely, especially when they can take real‑world actions.
Observability & debugging
Build tracing, logging, dashboards, and replay tools to understand agent behavior, diagnose failures, and iterate on policies and prompts.
Design experiments to compare agent architectures, policies, and tool sets; iterate based on offline and online metrics and qualitative user feedback.
Qualifications
4+ years in software engineering, ML engineering, or applied AI roles, including experience shipping systems that rely on LLMs or other ML components.
Strong programming skills in Python and experience building backend services (REST/gRPC, microservices, or similar).
Solid understanding of system design basics: latency, throughput, reliability, and failure modes.
Hands‑on experience working with LLM‑based applications (e.g., chatbots, copilots, automation tools, or internal agent‑like systems).
Familiarity with at least one agentic or orchestration framework (e.g., LangChain, Autogen, CrewAI, custom in‑house frameworks), or evidence of having built similar functionality yourself.
Ability to reason about complex multi‑step flows, failure modes, and edge cases.
Comfortable diagnosing issues that span prompts, tools, infra, and product logic.
Bonus Points
Experience designing multi‑agent or multi‑stage workflows (e.g., planner/solver/critic architectures).
Background integrating LLMs with transactional systems, internal tools, or external APIs.
Exposure to safety/guardrail systems: policy engines, content filters, or constrained tool execution.
Familiarity with cloud platforms, containers (Docker), and observability tools (metrics, tracing, logging).
What we offer
Opportunities for career advancement and personal development
Access to a diverse range of training programs
Performance‑based rewards that celebrate your achievements
Flexibility with a hybrid work model (3:2) that blends home and office life
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