GenAI Developer – Credit Risk and Fraud Platform (Banking)

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.ResponsibilitiesDesign and implement LangChain and LangGraph based agent workflowsBuild Python services exposing GenAI capabilities via secure APIsIntegrate LLMs with ML model outputs and structured enterprise dataDevelop RAG pipelines and vector based retrieval mechanismsImplement guardrails, validation layers, and evaluation logic for regulated outputsCollaborate with ML engineers and data scientists on end to end workflowsSupport deployment, monitoring, and optimisation in production environmentsEnsure explainability, traceability, and reliability of GenAI outputsRequirementsStrong hands on Python experience in backend or AI driven systemsCommercial experience building LLM based or GenAI solutionsPractical knowledge of LangChain and LangGraphExperience with FastAPI or Flask and REST API designUnderstanding of RAG architectures and vector databasesExperience with prompt engineering and agent design patternsKnowledge of secure API development practicesAbility to work in regulated, high availability environmentsFluent English for professional collaborationNice to haveExperience in banking, credit risk, or fraud prevention domainsExposure to ML model integration in production systemsExperience with monitoring and evaluation frameworks for LLMsBackground in distributed or microservices architecturesBenefitsSolid, competitive salaryWork in a multinational environment on international projectsComprehensive healthcareLong-term B2B contract with a stable project pipelineRemote work modelOriginally posted on Himalayas

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.ResponsibilitiesDesign and implement LangChain and LangGraph based agent workflowsBuild Python services exposing GenAI capabilities via secure APIsIntegrate LLMs with ML model outputs and structured enterprise dataDevelop RAG pipelines and vector based retrieval mechanismsImplement guardrails, validation layers, and evaluation logic for regulated outputsCollaborate with ML engineers and data scientists on end to end workflowsSupport deployment, monitoring, and optimisation in production environmentsEnsure explainability, traceability, and reliability of GenAI outputsRequirementsStrong hands on Python experience in backend or AI driven systemsCommercial experience building LLM based or GenAI solutionsPractical knowledge of LangChain and LangGraphExperience with FastAPI or Flask and REST API designUnderstanding of RAG architectures and vector databasesExperience with prompt engineering and agent design patternsKnowledge of secure API development practicesAbility to work in regulated, high availability environmentsFluent English for professional collaborationNice to haveExperience in banking, credit risk, or fraud prevention domainsExposure to ML model integration in production systemsExperience with monitoring and evaluation frameworks for LLMsBackground in distributed or microservices architecturesBenefitsSolid, competitive salaryWork in a multinational environment on international projectsComprehensive healthcareLong-term B2B contract with a stable project pipelineRemote work modelOriginally posted on Himalayas