Jr. AI Model Engineer (Agentic Systems & Orchestration)
Role details
Job location
Tech stack
Job description
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
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Design and implement agents Build agents that can plan tasks, call tools/APIs, decompose problems, and iterate based on feedback and intermediate results.
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Orchestration & routing Develop orchestration services that coordinate multiple models, agents, and tools (e.g., planners, executors, critics, evaluators), including policy logic and routing decisions.
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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.
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Context & state handling for agents Work closely with context management to maintain agent state across steps and sessions, including working memory, scratchpads, and long-running workflows.
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Reliability, safety & guardrails Implement checks, constraints, and fallback policies so agents behave predictably and safely, especially when they can take real-world actions.
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Observability & debugging Build tracing, logging, dashboards, and replay tools to understand agent behavior, diagnose failures, and iterate on policies and prompts.
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Experimentation & iteration Design experiments to compare agent architectures, policies, and tool sets; iterate based on offline and online metrics and qualitative user feedback.
Requirements
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2+ years in software engineering, ML engineering, or applied AI roles, including experience shipping systems that rely on LLMs or other ML components.
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Strong programming skills in Python and experience building backend services (REST/gRPC, microservices, or similar).
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Solid understanding of system design basics: latency, throughput, reliability, and failure modes.
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Hands-on experience working with LLM-based applications (e.g., chatbots, copilots, automation tools, or internal agent-like systems).
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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.
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Ability to reason about complex multi-step flows, failure modes, and edge cases.
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Comfortable diagnosing issues that span prompts, tools, infra, and product logic.
Bonus Points
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Experience designing multi-agent or multi-stage workflows (e.g., planner/solver/critic architectures).
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Background integrating LLMs with transactional systems, internal tools, or external APIs.
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Exposure to safety/guardrail systems: policy engines, content filters, or constrained tool execution.
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Familiarity with cloud platforms, containers (Docker), and observability tools (metrics, tracing, logging).
Benefits & conditions
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
- Electric car salary sacrifice scheme
- Life insurance
