AI Technical Lead

Luxoft; Greater London; On-site; GBP 120,000 - 180,000; Full time

Job summary

Luxoft is leading the development of a solution to generate investment insights from sales and research materials using advanced Agentic AI capabilities. The project focuses on rapid, high-quality client meeting preparations and scalable, secure cloud architectures.

The role involves architecting production-grade LLM orchestration, RAG pipelines, and end-to-end infrastructure lifecycles within AWS. You will work closely with stakeholders to translate strategic goals into practical

Qualifications

• Over 10 years of professional software development experience.
• Advanced Python and TypeScript skills with modern frameworks.
• Hands-on with agentic workflows using LangGraph or LangChain.
• Proven production AWS infrastructure experience (ECS Fargate, Lambda, SQS).
• Cloud architecture via IaC tools (CDK or Terraform).
• A relational + graph/vector database setup (Aurora/Neptune).
• Proficient with prompt engineering and AI tooling in production.
• Experience in agile, enterprise-scale AI deployments.

Responsibilities

• Lead architecture and implementation of production-grade LLM orchestration and multi-agent systems.
• Oversee enterprise RAG pipelines, semantic chunking, and vector DB integrations.
• Implement evaluation and observability to monitor latency, costs, drift, and accuracy.
• Design, deploy, and maintain secure, scalable AWS cloud systems (ECS Fargate, Lambda, SQS, Aurora, Neptune).
• Embed IaC and deployment pipelines into the development workflow.
• Collaborate with business stakeholders, product managers, and engineering teams to translate goals into technical reality.

Skills

10+ years of software development

Python (asyncio, FastAPI)

TypeScript (Next.js/React)

LangGraph / LangChain

AWS (ECS Fargate, Lambda, SQS)

IaC (AWS CDK or Terraform)

Aurora & Neptune databases

CLI tooling (Claude Code, Copilot CLI)

Agile production environments

Mentoring engineers

Tools

Terraform

AWS CDK

GitHub Copilot CLI

Claude Code CLI

LangGraph tooling

Job description

Project description

Luxoft is initiating the development of a solution designed to generate investment insights based on sales and research materials. The solution will leverage advanced Agentic AI capabilities to significantly reduce the time required to prepare for client meetings and improve quality of the insights.

Responsibilities

• Lead the architecture and implementation of production-grade LLM orchestration, multi-agent systems, and autonomous coding workflows
• Oversee the development of enterprise Retrieval-Augmented Generation (RAG) pipelines, semantic chunking strategies, and vector database integrations
• Implement strict evaluation and observability frameworks to monitor production latency, API costs, system drift, and model accuracy
• Drive the design, deployment, and ongoing maintenance of secure, scalable, and resilient cloud systems on AWS leveraging ECS Fargate, Lambda, SQS, Aurora, and Neptune
• Own the end-to-end infrastructure lifecycle by embedding robust Infrastructure-as-Code (IaC) and deployment pipelines directly within the development workflow
• Act as the primary technical liaison between business stakeholders, product managers, and the engineering team to translate strategic goals into technical realities

SKILLS

Must have

• 10+ years of professional software development experience.
• Advanced proficiency in Python (asyncio, FastAPI) and TypeScript (Next.js/React, serverless execution layers)
• Hands-on experience building complex, stateful agentic workflows using LangGraph or LangChain
• Proven track record architecting, provisioning, and managing your own production infrastructure on AWS, specifically utilizing ECS Fargate, Lambda, and SQS
• Experience defining cloud architecture programmatically using advanced Infrastructure-as-Code (IaC) tools like AWS CDK or Terraform (Python/TypeScript preferred)
• Experience managing relational databases (preferably Aurora) alongside graph or vector backends (such as Neptune)
• Power-user fluency with advanced command-line AI interfaces (Claude Code CLI, GitHub Copilot CLI) with a deep understanding of prompt engineering and context window management
• Experience operating in an agile setting, deploying and maintaining AI/LLM applications in a live, enterprise-scale production environment
• Accountable for results, with excellent communication skills to mentor engineers and defuse technical friction

Nice to have

• Highly desirable: experience with AgentCore, AWS Neptune, Amazon API gateway
• Familiarity with ML fundamentals relevant to content generation (embeddings, tokenization, evaluation, fine tuning/LoRA, prompt+retrieval evaluation).