Senior AI Engineer: Agentic Systems & Production LLMs

STARLIMS; Netherlands; On-site; EUR 90,000 - 150,000; Full time

Job summary

STARLIMS is building AI-enabled agents for enterprise-grade platforms used in quality manufacturing, life sciences, public health, forensics, and environmental sciences. This role focuses on agent platform runtime and building multi-step, auditable agentic workflows with human-in-the-loop oversight.

Ideal candidates have 6+ years in software engineering, strong backend/cloud skills (AWS), and hands-on experience with LLM tools, APIs, and multi-step orchestration.

Qualifications

• 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.

Responsibilities

• 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.
• 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.
• Close the loop: turn user corrections and overrides into signals that measurably improve the agent.
• 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.
• 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.
• 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
• 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

Skills

Production LLM systems

Tool-using workflows

TypeScript

Python

AWS

Debugging non-deterministic systems

Tools

AWS Lambda

Terraform

Kubernetes

Temporal

Step Functions

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Job description

STARLIMS is building AI-enabled agents for enterprise-grade platforms used in quality manufacturing, life sciences, public health, forensics, and environmental sciences. This role focuses on agent platform runtime and building multi-step, auditable agentic workflows with human-in-the-loop oversight.

Ideal candidates have 6+ years in software engineering, strong backend/cloud skills (AWS), and hands-on experience with LLM tools, APIs, and multi-step orchestration.