Job Title: Lead Engineer - AI Enablement (AWS, Python/TypeScript, AI Gateway)
Location: Remote (UK-based)
Rate: Negotiable / Competitive (Inside IR35)
Duration: 6 Months Initial
Clearance: SC Clearance Required - this must be active and have been used on a government project within the last 12 months.

Overview:

We are seeking a Lead Engineer (AI Enablement) to guide an engineering team delivering an Enterprise AI Gateway and central generative AI capabilities for a high-profile public sector organisation. The role combines software design, development management, technical assurance, and hands-on engineering across cloud platforms, LLM integration, and agentic tooling.

Key Responsibilities:

• Lead the AI Enablement engineering team, set engineering standards, and conduct technical assurance and approvals.
• Guide software design for production backend services, APIs, identity/access controls, and agentic workflows.
• Line manage engineers, manage performance, support CPD, lead technical recruitment, and maintain workforce plans.
• Oversee delivery across AWS Bedrock, AI Gateways, model integration, observability, cost controls, and security.
• Partner with Architecture, Cyber Security, FinOps, and Operations to deliver secure, resilient live services.

Key Skills & Experience Required:

• Proven track record leading software engineering teams, managing delivery, and line-managing engineers.
• Hands-on proficiency in modern languages: Python, TypeScript / Node.js, Java, or Go.
• Practical experience building AI-enabled services, integrating LLMs, model evaluation, and prompt/context management.
• Hands-on experience with AWS (specifically AWS Bedrock or comparable foundation model platforms).
• Strong knowledge of OAuth2/OIDC, IAM, RBAC, and telemetry (OpenTelemetry, Splunk, Prometheus).
• Active SC Clearance (or immediate eligibility).

Desirable Skills:

• Experience with Cloudflare AI Gateway or custom AI proxy/gateway technologies.
• Experience building AI agents, tool-using systems, or Model Context Protocol (MCP) integrations.
• Experience with RAG, embeddings, vector search, or enterprise knowledge integration.
• Infrastructure automation using Terraform, Docker, Kubernetes/ECS, and CI/CD pipelines.