Senior AI Platform Deployment Engineer

Moneybox; England; On-site; GBP 90,000 - 130,000; Full time

Job summary

Moneybox is building a new AI Deployment team to deliver on a company-wide AI Platforms strategy. You will be a forward-deployed senior engineer focusing on deploying AI safely and producing production-grade Python across the modern AI stack, including orchestration, RAG, guardrails, and cost optimization.

You will embed with departments, deploy AI components to production, and help turn engagement patterns into self-serve tooling on the AI Platforms stack.

Qualifications

• 5+ years of software engineering with meaningful production ownership.
• Has built and shipped LLM-powered systems that ran in production.
• Production-grade Python as your primary language.
• LLM-powered systems in production: real-world experience working with models via APIs - harnesses, orchestration, structured output, tool use and agents, RAG where appropriate.
• Evals and quality: designing evaluation sets, measuring accuracy, recall and precision for LLM steps, regression-testing prompts and workflows.
• Safety and guardrails in practice: PII handling, data-boundary discipline, prompt-injection awareness, human-in-the-loop design.
• Cost and performance optimisation: 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: consultancy, forward-deployed engineering, solutions engineering, or embedded or platform roles serving non-engineering users.
• Experience with Azure and/or .NET. We host on Azure and our core stack is .NET, so willingness to integrate with both is required.
• Experience with agent hosting and sandboxing platforms, LLM or MCP gateways, or agentic workflow orchestration tooling.
• Experience in financial services or another regulated environment.
• Experience deploying models built by a data science team into customer-facing production systems.

Responsibilities

• Own engagement delivery end to end: scope, design, build, deploy, handover and ownership model from prototype to production.
• Engineer AI solutions properly: pipelines, LLM API integration, evals, guardrails, monitoring, and cost/accuracy optimisation.
• Graduate tools into business systems: rebuild team-made tools as owned systems under full SDLC.
• Deploy ML-built components into production: serving, integration with Moneybox platform, and coordination with Decisioning and Data Science teams.
• Build reusable capability: turn learnings into templates, playbooks, self-serve workflows on the AI Platforms stack.
• Raise the bar: collaborate with embedded specialists to ensure long-term capability retention.

Skills

Production ownership

Python production

LLM systems

Evals & QA

Cost optimization

CI/CD & monitoring

Azure

-.NET integration

Tools

Azure

.NET

Job description

Moneybox is building a new AI Deployment team to deliver on a company-wide AI Platforms strategy. You will be a forward-deployed senior engineer focusing on deploying AI safely and producing production-grade Python across the modern AI stack, including orchestration, RAG, guardrails, and cost optimization.

You will embed with departments, deploy AI components to production, and help turn engagement patterns into self-serve tooling on the AI Platforms stack.