Lead Engineer | ResGEN Team

Lead Engineer: GenAI Platform

You'd be defining the engineering foundations underneath an organisation's generative AI capabilities, and then building on them yourself. Hands-on engineering with a leadership dimension attached: architectural direction, coaching the engineers around you, and the technical decisions that determine whether GenAI services stay reliable once they're actually in production and actually being used.

The interesting constraint is that these services have to be compliant and safe as well as scalable. That's a different engineering problem from building GenAI in a startup, and it's where most of the hard design questions live.

The environment

Our client is an international bank building out generative AI capability at scale. You'd work across engineering, security, architecture and product management: a genuinely cross-cutting position, because the platform touches all four.

The engineering culture is one where technical direction is argued rather than handed down. You'd be one of the people expected to shape it, including in quarterly planning and roadmap discussions.

What you'll do

Lead the design and implementation of scalable, secure and reliable GenAI services.

Guide technical direction and architectural decision-making.

Drive improvements in engineering practice, platform reliability and operational excellence.

Spot the gaps, risks and opportunities across the platform landscape before they become incidents.

Coach and mentor engineers through pairing, code review and technical discussion.

Set best practice for DevOps, cloud engineering and observability.

Make sure what gets built is deployed, maintained and properly operated in production.

Contribute to quarterly planning and the technical roadmap.

Tech stack

Core: Python · FastAPI · Azure · Terraform and/or Bicep · CI/CD and automation · monitoring, logging & observability

Also in the mix: LLM-based systems and GenAI platforms · Azure AI capabilities · identity & access management · Kafka and event-driven architectures

Must-haves

Proven software engineering and DevOps experience, including delivering and operating production-grade cloud solutions.

Strong Python and modern back-end development, with FastAPI or a comparable framework.

Strong Azure cloud experience.

Advanced CI/CD, automation and Infrastructure as Code with Terraform and/or Bicep.

Real depth in monitoring, logging and observability: operational excellence as daily practice rather than a maturity model.

A track record of getting cloud-native solutions into production, not just built.

Strong advantage

GenAI platforms, LLM-based systems and AI application architectures.

Azure AI capabilities and AI governance concepts.

Identity and access management.

Event-driven, streaming or asynchronous architectures, with Kafka or similar.

You're the person the team turns to when the problem is complex, the priorities have moved and nobody's quite sure what the right call is. You think past the ticket in front of you, you'll challenge an assumption when it deserves it, and you get something out of making the engineers around you better.

Good to know

A pre-employment screening is part of the process, as is standard for the financial sector.

Working language is English; Dutch is not required.

You'll need a valid EU work permit or existing right to work in the Netherlands.