FDE AI/ Solutions Architect (AI, Python/Data)

Responsibilities

• Take the seat
• Sit with the client and the Forward Deployed Executive at the start of an engagement. Learn the function from inside, not from a requirements doc, and redesign the function from first principles.
• Reach working fluency in a new domain — insurance underwriting, healthcare revenue cycle, asset flow.
• Design and ship production GenAI systems into the customer’s environment (cloud-native data, LLM-based, and agentic AI solutions).
• Implement and optimize RAG systems for production use cases
• Build the evaluation harness before you build the feature. Define what working means, instrument it, and let the evals drive the design.
• Write production code across the stack — AI, backend services, data pipelines. We choose tools to fit the customer.
• Take systems to production on AWS (GCP or Azure where the customer requires it): containerised, CI/CD, automated testing, monitoring, and maintainable after we leave. Hand the system over to the client.
• Start from the blueprint, and feed the blueprint. What you learn in the field becomes the baseline the next engagement starts from.
• Lead architecture reviews, produce technical design documents, and contribute to standards. Mentor engineers and share knowledge across the team.

Languages