Forward Deployed Engineer

Job Description

We are hiring a Forward Deployed Engineer to help bring AI into real business operations. The role sits between engineering, consulting and business change. You will build and run applications for the IFS M&A Group and deliver production AI solutions to acquired companies. You will work with their business and technical stakeholders to understand the problem, prototype quickly, connect to existing systems, and deliver implementations that work at scale. 

You work independently with limited guidance on assigned projects, within the group's approved architecture, security and data standards. You escalate decisions that fall outside those guidelines to your manager. 

Key Responsibilities 

• Deliver assigned AI projects and workstreams, from discovery through design, build, deployment, verification, training and support. Priorities and scope are agreed with your manager. 

• Support discovery with business and technical stakeholders to understand workflows, systems and desired outcomes, and help identify suitable AI use cases. 

• Analyse non-routine requirements, recommend practical solution designs, and implement them as tested code. Prototype quickly to validate a use case. 

• Build integrations that connect AI platforms to existing applications, APIs and data sources, using service identities with the narrowest scopes and following approved security and data governance policies. 

• Ship AI features that are scoped to the user, name sources and models on every answer, and are tested before release. 

• Build agentic systems that automate processes and use enterprise tools within defined guardrails. 

• Take solutions from prototype to production and run them: jobs, backups, monitoring, access and incident write-ups. 

• Train users and support adoption. Measure results against the objectives agreed at the start of each project. 

• Recommend models and platforms within the group's approved standards. Contribute lessons learned from acquired-company projects to team best practices and process improvements. 

• Report progress, trade-offs and outcomes clearly to stakeholders and project leads. 

• Provide guidance to junior colleagues where needed. 

Qualifications

Requirements 

• In-depth expertise in AI/software engineering, with a solid understanding of related areas (data, cloud, security) and business context. 

• Experience shipping at least one system to production and measuring its operational or business impact. 

• Experience building an LLM application used by real users, covering tool use, retrieval and prompt or context design. 

• Experience with API integrations between AI platforms and enterprise systems (e.g. Salesforce, HubSpot, NetSuite, Databricks) and the data governance that goes with them. 

• Python backend (FastAPI or similar), working React/TypeScript, SQL, one cloud (Azure preferred), infrastructure as code and CI/CD. 

• Ability to work independently on non-routine problems, recommend practical solutions, and escalate when a decision is outside agreed guidelines. 

• Clear written and spoken communication with both technical and business stakeholders. 

• A habit of verifying results, with numbers checked before they are reported. 

Nice to Have 

• Experience in a forward-deployed or embedded engineering role. 

• Familiarity with RevOps, FP&A or sales operations. 

• Agent experience in production, ideally with Model Context Protocol. 

• Azure experience (Container Apps, Entra, Key Vault, Terraform, Azure DevOps). 

• Working French or Dutch. 

Additional Information