Coltech
Lead AI Platform Engineer
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Lead AI Platform Engineer (Finance AI Platform)
Location: Sheffield, UK (Hybrid – 3 Days Onsite per Week)
Contract Type: Contract / Long-Term Engagement
Industry: Financial Services / AI Transformation
Role Overview
We are seeking an experienced Lead AI Platform Engineer to play a key role in the development of a next-generation Finance AI Platform. This is a hands-on technical leadership position focused on building scalable AI-enabled enterprise applications, establishing engineering standards, and accelerating the adoption of Generative AI across business-critical platforms.
The successful candidate will bring deep expertise in cloud-native software engineering, AI application development, and modern platform architecture, with a proven ability to lead engineering teams while remaining actively involved in solution design and implementation.
Key Responsibilities
- Lead the design, development, and deployment of AI-enabled enterprise applications.
- Build and scale AI platform capabilities supporting LLM, RAG, and Agentic AI solutions.
- Define reusable AI engineering frameworks, patterns, and development standards.
- Design and implement secure, scalable, and production-ready AI architectures.
- Integrate Large Language Models (LLMs) into existing enterprise applications and workflows.
- Drive the adoption of AI orchestration frameworks and agent-based architectures.
- Collaborate closely with architects, product owners, and engineering teams to deliver high-quality solutions.
- Establish best practices around AI governance, observability, monitoring, security, and performance.
- Conduct code reviews, mentor engineering teams, and provide technical leadership across multiple workstreams.
- Support CI/CD, DevOps, and cloud-native delivery practices throughout the software development lifecycle.
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Required Skills & Experience
- 12+ years of software engineering experience.
- Strong hands-on expertise in Java and/or Python.
- Extensive experience developing cloud-native applications on Azure, AWS, or GCP.
- Strong background in:
- Kubernetes
- Docker
- Microservices Architecture
- REST APIs
- Event-Driven Systems
- CI/CD and DevOps Practices
- Proven experience implementing:
- Large Language Models (LLMs)
- Retrieval-Augmented Generation (RAG)
- Agentic AI Solutions
- AI Workflow Orchestration
- Hands-on experience with one or more of:
- LangChain
- LangGraph
- Semantic Kernel
- AutoGen
- CrewAI
- Similar AI Frameworks
- Strong understanding of enterprise-scale architecture, security, resilience, and operational excellence.
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Preferred Experience
- Experience with:
- Azure OpenAI
- OpenAI
- Anthropic Claude
- Google Gemini
- Exposure to vector databases such as Pinecone, Weaviate, Milvus, pgvector, or similar.
- Experience with AI observability, monitoring, and governance platforms.
- Financial Services, Banking, Treasury, or FinTech domain experience.
- Experience establishing AI engineering standards and best practices across multiple product teams.
Candidate Profile
- Hands-on technical leader who enjoys building and delivering solutions.
- Strong engineering mindset with the ability to influence technical direction.
- Comfortable working within established enterprise architecture and delivery frameworks.
- Able to mentor engineers and drive technical excellence across teams.
- Strong stakeholder engagement and communication skills.
- Passionate about building secure, scalable, production-grade AI platforms.
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