Forward Deployed Engineer

g2 Recruitment; Amsterdam; Hybrid; EUR 70,000 - 110,000; Full time

Job summary

g2 Recruitment in Amsterdam is looking for a Forward Deployed AI Engineer to join one of our deployment teams and translate client workflows into production AI solutions.

You will prototype AI agents, integrate with ERP/CRM and SaaS, deploy in customer environments, and ensure observability and reliability.

Strong Python, LLM systems, cloud and enterprise integrations are required; this is a hybrid role with collaboration across teams and clients.

Qualifications

• Hands-on experience with Python, APIs, databases, Git, testing, and CI/CD.
• Experience with LLMs, tool calling, RAG, structured outputs, orchestration and evaluation.
• Production AI experience: observability, guardrails, human-in-the-loop workflows.
• Cloud/infrastructure experience, ideally Azure/AWS/GCP, with Docker/Kubernetes.
• Enterprise integrations with REST APIs, SSO, SAP/ServiceNow/Salesforce/M365.

Responsibilities

• Understand the problem by mapping real workflows with customer teams.
• Build AI agents, integrations, workflows, and supporting software using LLMs and enterprise data.
• Integrate deployed solutions with ERP, CRM, SaaS, APIs, databases and internal tooling.
• Deploy and monitor systems in production, iterating based on real usage.

Skills

Python

LLM & agentic systems

Production AI

Cloud & infrastructure

Enterprise integrations

Tools

LangGraph

LangChain

LlamaIndex

MCP

Langfuse/LangSmith

Job description

Location: Amsterdam / Netherlands

Working model: Hybrid

Extension: likely depending on project pipeline

We are looking for a Forward Deployed AI Engineer to join one of our deployment teams.

We are a Dutch AI engineering company working with large European organisations to put AI into the operational systems where work actually happens. We build software that allows AI systems to perform real work inside businesses.

That means connecting agents to ERP systems, internal APIs, documents, databases and business applications; giving them carefully controlled access to tools; evaluating their behaviour; putting humans in the right places; and getting the resulting system into production.

What you will do:

1. Understand the problem: Work directly with customer teams to map real workflows, identify where AI can create value, and turn ambiguous problems into buildable solutions.

2. Build: Rapidly prototype and develop AI agents, integrations, workflows and supporting software using LLMs, APIs, enterprise data and existing systems.

3. Integrate: Connect what you build to the customer's real environment — ERP, CRM, SaaS, APIs, databases, identity and internal tooling.

4. Deploy: Work alongside customer engineering teams to get systems into production, monitor them in the real world and iterate based on actual usage.

Technical experience

You should have strong hands-on experience with:

• Python and modern software engineering, including APIs, databases, Git, testing and CI/CD.
• LLM and agentic systems, including tool calling, RAG, structured outputs, orchestration and evaluation.
• Production AI, including observability, guardrails, human-in-the-loop workflows and reliability.
• Cloud and infrastructure, ideally Azure, AWS or GCP, with Docker/Kubernetes experience.
• Enterprise integrations, including REST APIs, authentication/SSO and systems such as SAP, ServiceNow, Salesforce or Microsoft 365.

Experience with frameworks such as LangGraph, LangChain, LlamaIndex, MCP, Langfuse or LangSmith is useful, but we care more about what you have actually shipped than which tools you have used.

If you are excited by the prospect of turning agentic AI prototypes into reliable systems that operate inside real enterprise environments, get in contact with [e-mail]