Forward Deployed Engineer

In this role you will lead the production deployment of AI-powered solutions at Moneybox, turning prototypes into reliable, scalable systems. You’ll partner with departments to embed AI into business workflows and deploy components built by ML and Decisioning teams into live customer features. You will shape safe, self-serve AI capabilities across the platform, balancing performance, cost, and governance. This is a hands-on, production-focused engineering role with a strategic impact on how Moneybox leverages AI at scale.

• Own engagement delivery end-to-end from scoping to production handover
• Engineer AI solutions including pipelines, LLM API integration, evals, guardrails, monitoring and cost optimization
• Graduate shared tools into robust business systems under full SDLC
• Deploy ML-built components into production in collaboration with Decisioning and Data Science
• Build reusable tooling, templates, playbooks, and self-serve workflows on the AI Platforms stack
• Collaborate with embedded specialists to raise the capability and ensure long-term ownership in Moneybox
• Deliver departmental engagements with measurable business value (time saved, cost avoided, risk reduced) and deploy at least one ML capability with proper evals and monitoring in first three months

• 5+ years of software engineering with production ownership
• Built and shipped LLM-powered systems in production
• Production-grade Python as primary language
• Experience with LLMs via APIs including orchestration, tool use, agents, RAG
• Designing evals and measuring accuracy/recall/precision for LLM steps
• Safety and guardrails in practice: PII handling, data-boundary discipline, prompt-injection awareness, human-in-the-loop design
• Cost and performance optimization: model selection, caching, batching, token economics, latency budgets
• Deployment and operations: CI/CD, containerisation, monitoring and alerting for AI workloads
• Data processing fundamentals: pipelines, transformation, validation, anomaly handling
• Customer- or stakeholder-facing delivery experience via consultancy or embedded/platform roles

• Comfortable in ambiguity
• Strong partner to non-technical owners
• Platform thinking
• Azure (Desirable)
• .NET (Desirable)
• Experience with agent hosting and sandboxing platforms