This is a remote position.

We are looking for a GenAI Developer to join a production critical decision intelligence platform within the banking domain. The role focuses on building and scaling GenAI services that operate directly in credit risk and fraud prevention workflows, supporting high volume, regulated decision environments.The platform combines machine learning, large scale data processing, and agent based GenAI orchestration to generate decision support, explanations, and structured outputs consumed by lending engines, fraud systems, and internal risk teams. The environment is live in production and operates under strict security, performance, and regulatory constraints.

Responsibilities

  • Design and implement LangChain and LangGraph based agent workflows
  • Build Python services exposing GenAI capabilities via secure APIs
  • Integrate LLMs with ML model outputs and structured enterprise data
  • Develop RAG pipelines and vector based retrieval mechanisms
  • Implement guardrails, validation layers, and evaluation logic for regulated outputs
  • Collaborate with ML engineers and data scientists on end to end workflows
  • Support deployment, monitoring, and optimisation in production environments
  • Ensure explainability, traceability, and reliability of GenAI outputs

Requirements

  • Strong hands on Python experience in backend or AI driven systems
  • Commercial experience building LLM based or GenAI solutions
  • Practical knowledge of LangChain and LangGraph
  • Experience with FastAPI or Flask and REST API design
  • Understanding of RAG architectures and vector databases
  • Experience with prompt engineering and agent design patterns
  • Knowledge of secure API development practices
  • Ability to work in regulated, high availability environments
  • Fluent English for professional collaboration
Nice to have
  • Experience in banking, credit risk, or fraud prevention domains
  • Exposure to ML model integration in production systems
  • Experience with monitoring and evaluation frameworks for LLMs
  • Background in distributed or microservices architectures

Benefits

  • Solid, competitive salary
  • Work in a multinational environment on international projects
  • Comprehensive healthcare
  • Long-term B2B contract with a stable project pipeline
  • Remote work model