Senior AI Engineer (Netherlands)

About This Opportunity

We are representing a confidential software organization building AI capabilities into an enterprise platform used across quality manufacturing, life sciences, public health, and regulated environments. This Senior AI Engineer role focuses on agentic systems—software that reasons over tasks, calls tools, works through multiple steps, and presents results for human review and approval.

Our client's users operate under strict accuracy, traceability, and validation requirements. The core engineering challenge is making non-deterministic systems reliable, observable, and controllable enough to be trusted, tested, and shipped in production environments.

Responsibilities

Agent Platform & Runtime

• Design and build the runtime environment for agent execution: planning and execution loops, tool calling, state management, durable execution, and failure recovery
• Build the layer through which agents safely access platform data and external systems
• Design coordination, delegation, and handoff across agents and workflows
• 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

• Transform domain workflows from expert conversations into working agents: goals, actions, execution flow, failure handling, and success criteria
• Ground agent decisions and outputs in authoritative enterprise data rather than relying solely on model knowledge
• Implement human-in-the-loop by design, including approval gates, override capture, uncertainty handling, and clear evidence for agent decisions
• Turn user corrections and overrides into signals that measurably improve agent performance

Evaluation & Reliability

• Build evaluation harnesses for multi-step behavior: 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
• 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

Integration & Data

• Integrate agents with platform APIs and third-party enterprise systems
• Build retrieval and context pipelines that turn fragmented enterprise data into reliable, permission-aware agent context
• Design controlled execution paths for automated actions with complete, traceable audit trails

Platform & Infrastructure

• Build and operate backend services on AWS (Lambda, API Gateway, DynamoDB, Step Functions)
• Own significant parts of the system architecture and contribute to key technical decisions
• Contribute to infrastructure-as-code and deployment pipelines

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 multi-step runs
• 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
• Comfort debugging across distributed and non-deterministic systems
• Ability to make explicit tradeoffs between accuracy, latency, reliability, and cost
• Experience working in ambiguous problem spaces where the right architecture isn't obvious yet
• Track record of owning production systems end-to-end

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

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)

How We Work With You

Candidates apply directly through Get A Job.ai. Our talent team will screen your application and conduct an initial interview to understand your background and goals. If there's a strong match, we will submit your profile to our client for consideration. Please do not contact the client directly—all communication flows through our recruiting team to ensure a professional and coordinated process.

Pay

Compensation details will be discussed during the screening process based on experience and qualifications.

Equal Opportunity

Get A Job.ai is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status.