Lead AI Engineer

Test Triangle; Sheffield; On-site; GBP 120,000 - 180,000; Full time

Job summary

Test Triangle is seeking a highly experienced Lead AI Platform Engineer to drive the engineering and implementation of AI capabilities within a Finance AI platform. This hands‑on technical leadership role focuses on establishing scalable AI engineering patterns, accelerating delivery, and mentoring development teams.

The ideal candidate will combine strong cloud‑native engineering expertise with practical experience building and integrating GenAI and Agentic AI solutions into enterprise

Qualifications

• 12+ years of software engineering experience.
• Strong expertise in Java and/or Python.
• Experience building cloud-native applications on Azure, AWS, or GCP.
• Knowledge of Kubernetes, Microservices, APIs, Event-Driven Architecture, and DevOps practices.
• Hands-on experience with LLM integration, RAG architectures, AI orchestration frameworks, and Agentic AI solutions.
• Experience with AI frameworks and tools such as LangChain, LangGraph, Semantic Kernel, AutoGen, CrewAI, or equivalent.

Responsibilities

• Lead the implementation of AI-enabled applications and platform capabilities.
• Establish reusable patterns, frameworks, and best practices for AI engineering.
• Design and oversee LLM, RAG, and Agentic AI integrations within enterprise environments.
• Collaborate with architects and engineering teams to ensure scalable, secure, and maintainable solutions.
• Define standards for AI observability, governance, security, and performance.
• Mentor engineers and provide technical leadership across AI development initiatives.
• Contribute hands-on to solution design, development, code reviews, and production deployment.

Skills

Java

Python

Cloud-native architecture

Kubernetes

DevOps practices

LLM integration

Agentic AI

Tools

LangChain

LangGraph

Semantic Kernel

AutoGen

CrewAI

Job description

We are seeking a highly experienced Lead AI Platform Engineer to drive the engineering and implementation of AI capabilities within a Finance AI platform. This is a hands‑on technical leadership role focused on establishing scalable AI engineering patterns, accelerating delivery, and mentoring development teams. The ideal candidate will combine strong cloud‑native engineering expertise with practical experience building and integrating GenAI and Agentic AI solutions into enterprise platforms.

Key Responsibilities

• Lead the implementation of AI-enabled applications and platform capabilities.
  
• Establish reusable patterns, frameworks, and best practices for AI engineering.
  
• Design and oversee LLM, RAG, and Agentic AI integrations within enterprise environments.
  
• Collaborate with architects and engineering teams to ensure scalable, secure, and maintainable solutions.
  
• Define standards for AI observability, governance, security, and performance.
  
• Mentor engineers and provide technical leadership across AI development initiatives.
  
• Contribute hands‑on to solution design, development, code reviews, and production deployment.
  

Required Skills

• 12+ years of software engineering experience, with strong expertise in Java and/or Python.
  
• Proven experience building cloud‑native applications on Azure, AWS, or GCP.
  
• Strong knowledge of Kubernetes, Microservices, APIs, Event‑Driven Architecture, and DevOps practices.
  
• Hands‑on experience with LLM integration, RAG architectures, AI orchestration frameworks, and Agentic AI solutions.
  
• Experience with AI frameworks and tools such as LangChain, LangGraph, Semantic Kernel, AutoGen, CrewAI, or equivalent.