GenAI Solution Architect

This is a remote position.

• Python, LangChain for LLM orchestration, LangGraph, LangSmith
  
• AWS Bedrock for model access (Anthropic among the providers), with Bedrock Knowledge Bases and Bedrock Guardrails
  
• AWS: ECS, Lambda, S3, API Gateway, DynamoDB, Cognito, EventBridge, WAF
  
• Twilio (telephony, in production)
  
• MCP and Agent-to-Agent integrations
  

• Owning the AI architecture underpinning the multi-market roll-out;
  
• Discovering the unknowns in new feature requirements — surfacing ambiguity, hidden assumptions, and unstated constraints before implementation starts;
  
• Identifying and mitigating technology risks early, well before they surface as development problems;
  
• Proving designs by building proofs of concept, and handing them to the development team as the basis for full implementation;
  
• Shaping the evaluation and observability architecture for the agentic system — this is a new area of the solution, and you will be expected to bring options and a point of view rather than inherit a design;
  
• Designing and iterating on multi-agent architectures, and defining integration standards for MCP servers and agent-to-agent communication;
  
• Working with the senior technical lead in Poland and the development team in India, supporting implementation day to day;
  
• Collaborating with the data and domain architects on the wider programme to deliver joined-up solution designs;
  
• Working closely with the Business Analyst to validate business designs and provide technical feedback;
  
• Advising on prompt engineering strategy, tool use design, and agent reliability across multiple languages and markets.
  

Requirements

• Advanced, production-level experience with LangChain, LangGraph, and LangSmith in Python;
  
• Hands-on experience implementing Model Context Protocol (MCP) and Agent-to-Agent (A2A) integrations;
  
• Solid experience with AWS, ideally including Bedrock, and comfort designing within a serverless and container-based AWS estate;
  
• A genuinely hands-on approach — you build the proof of concept yourself rather than delegating it;
  
• A considered view on GenAI evaluation and observability, and the ability to argue for an architectural approach in front of technical stakeholders;
  
• Proven ability to work with under-specified requirements: extracting the real need from stakeholders and making defensible decisions under uncertainty;
  
• Sound judgement in technology selection, with a track record of de-risking choices early rather than discovering problems in development;
  
• Ability to work effectively with a distributed, cross-timezone team and to communicate designs clearly to mid-level and junior engineers;
  
• Strong communication skills — able to translate complex AI concepts for technical and non-technical stakeholders;
  
• English proficiency at B2 level or above.
  

• Experience with telephony and call centre applications, particularly Twilio and voice/AI integration patterns;
  
• Experience scaling an AI product across multiple languages or markets;
  
• Background in enterprise AI platform architecture.