Gen AI Engineer

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• Design and build production-grade GenAI systems: multi-agent architectures, RAG pipelines over large/enterprise-scale document stores, and real-time systems used in daily business operations
  

• Build agentic systems that reason, retrieve, and act — not just conversational responders
  

• Work directly with client stakeholders to translate ambiguous business problems into scoped, deployable AI use cases
  

• Rapidly prototype and iterate on-site/embedded with the client, compressing the feedback loop between idea and working solution
  

• Own solutions end-to-end — architecture, implementation, evaluation, and handoff — rather than working purely from fixed specs
  

• Bridge technical and business conversations: explain trade-offs to non-technical stakeholders and translate priorities back into technical decisions
  

Requirements

• Strong GenAI expertise — hands-on experience with LLMs, prompt engineering, RAG, agentic frameworks, and multi-agent design; comfortable working across multiple model providers
  

• Core stack: Python, FastAPI/Django, and Azure or AWS
  

• Applied depth in the hard parts, e.g.:
  

  • Permission-aware retrieval at scale
    

  • Async task orchestration
    

  • LLM evaluation and observability
    

• Business understanding — able to grasp a client's operating model and pressure-test whether a proposed AI use case creates measurable value, not just technical novelty
  

• Forward-deployed mindset — thrives working embedded with clients rather than at arm's length; comfortable with ambiguity, direct client exposure, and fast iteration cycles typical of an FDE role
  

• Strong communication skills — able to run discovery sessions, present to leadership, and document decisions clearly.
  

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