Generative AI Engineer

This is a remote position.

• Turning functional designs into low-level technical designs that development teams can build from directly
  
• Running spikes and proofs of concept independently - scoping them, building them and reaching a clear conclusion
  
• Proving integration patterns to surrounding systems end to end: authentication, authorisation, secrets management and API contracts
  
• Designing and prototyping agent behaviour with LangChain and LangGraph; instrumenting, tracing and evaluating with LangSmith
  
• Implementing MCP integrations and agent-to-agent communication patterns
  
• Writing documentation and reference code clear enough for a distributed team to follow without you in the room
  
• Working alongside the tech lead and architects so that prototype decisions stay consistent with the target architecture
  
• Driving open questions to resolution across teams - raising the issue, convening the right people and closing the loop
  

Requirements

• Hands-on experience with LangChain, LangGraph and LangSmith — building, debugging and evaluating agent systems, not just familiarity
  
• Strong, current Python development skills
  
• Experience building interfaces to other systems, including authentication, authorisation and secrets management
  
• Practical experience implementing Model Context Protocol (MCP) integrations
  
• Experience with agent-to-agent (A2A) integration patterns
  
• Able to conduct proofs of concept independently, from scoping through to a documented conclusion
  
• Comfortable working closely with both a development team and solution architects
  
• Proactive communicator — able to set up meetings, chase answers across teams and resolve blockers without being asked
  
• Clear technical writing and example code that others can work from
  

• Experience with telephony and call centre applications - the platform uses Twilio
  
• Experience with multilingual or multi-market AI deployments
  
• RAG evaluation and answer-quality measurement at production scale
  
• Experience working with distributed teams across time zones
  
• Exposure to regulated or compliance-sensitive content domains
  

• Development teams start work with fewer open questions and fewer false starts
  
• Integration patterns are proven once and reused across markets, rather than rediscovered each time
  
• Low-level designs are specific enough to build from - and are actually used by the teams they were written for
  
• Technical unknowns surface and get resolved before they become delivery blockers
  

• Python
  
• LangChain, LangGraph, LangSmith
  
• Agentic RAG over product content; multi-language and multi-market
  
• MCP and agent-to-agent integration
  
• Authentication, authorisation and secrets management across system boundaries
  
• Twilio for telephony and call centre channels
  
• Working context
  
• Product owner, management and tech lead based in Poland
  
• English as the working language across the delivery team
  

Benefits