Senior AI Engineer (Netherlands) at Starlims Corporation | Remote Jobs

Design and build the runtime our agents execute on: planning and execution loops, tool calling, state management, durable execution, and failure recovery
Build the layer through which agents reach platform data and external systems safely
Design coordination, delegation, and handoff across agents and workflows where needed
Make agent behavior versionable, testable, measurable, and regression-safe across releases
Build reusable primitives so new agents are configured rather than rebuilt from scratch Building Agents (Core Focus)
Take a domain workflow from expert conversation to a working agent: goals, actions, execution flow, failure handling, and success criteria
Ground agent decisions and outputs in authoritative enterprise data rather than relying on model knowledge alone
Implement human-in-the-loop by design, including approval gates, override capture, uncertainty handling, and clear evidence for agent decisions. Agents recommend and draft; people decide
Close the loop: turn user corrections and overrides into signals that measurably improve the agent Evaluation & Reliability
Build evaluation harnesses for multi-step behavior, not single-response accuracy: task completion, tool-call correctness, groundedness, trajectory quality, and regression across model, prompt, and tool changes
Define production metrics for agent quality, reliability, latency, cost, and human intervention rates
Implement guardrails, fallbacks, timeouts, cost ceilings, and end-to-end observability and tracing across agent runs
Design safeguards against prompt injection, unsafe tool use, excessive permissions, data leakage, and other agent-specific security risks
Manage prompt evolution, model drift, and non-determinism while maintaining consistent, measurable system behavior across releases Integration & Data
Integrate agents with platform APIs and third-party enterprise systems already running in our customers’ environments
Build retrieval and context pipelines that turn fragmented enterprise data into reliable, permission-aware agent context
Design controlled execution paths for automated actions, with a complete, traceable audit trail Platform & Infrastructure
Build and operate backend services on AWS (Lambda, API Gateway, DynamoDB, Step Functions, etc.)
Own significant parts of the system architecture and contribute to key technical decisions
Contribute to infrastructure-as-code and deployment pipelines Tech Stack
Languages: TypeScript, Python
Backend: Node.js, Python, AWS Lambda, Step Functions
AI: OpenAI, Anthropic, MCP and related agent/tool protocols, embeddings and vector search
Frontend: React, Next.js, Tailwind CSS
Infrastructure: AWS, Terraform
Testing: Jest, Playwright, pytest What We’re Looking For Must Have
6+ years of software engineering experience, including production systems
Experience building production LLM systems, including tool-using or multi-step agentic workflows beyond simple prompting and chat interfaces
Strong understanding of LLM behavior, limitations, and failure modes, especially how errors compound across a multi-step run
Experience with LLM APIs, tool and function calling, and designing planning and execution loops
Experience evaluating and debugging non-deterministic systems
Solid backend and cloud experience (AWS or equivalent)
Proficiency in TypeScript and/or Python You Should Be Comfortable With
Debugging across distributed and non-deterministic systems
Making explicit tradeoffs between accuracy, latency, reliability, and cost
Working in ambiguous problem spaces where the right architecture isn't obvious yet
Owning production systems end-to-end
Choosing conventional software over AI when AI isn't the right solution Nice to Have
C#, Microsoft .NET Framework
Tool and interop protocols such as MCP
Evaluation pipelines and metrics built specifically for agentic systems
Experience in regulated or domain-heavy systems (validation, audit trails, controlled change)
Retrieval and grounding techniques for supplying agent context
Workflow and durable-execution platforms (Temporal, Step Functions, n8n, etc.)
Containerization and orchestration (ECS, EKS, Kubernetes)
Infrastructure as Code (Terraform or similar) STARLIMS is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, creed, religion, color, national or ethnic origin, citizenship, sex, sexual orientation, gender identity and expression, genetic information, veteran status, age or disability status.

Senior AI Engineer (Netherlands)

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