GenAI Engineer

Job DescriptionGenAI EngineerDesign and develop AI/ML and Generative AI solutions for banking use cases including fraud detection, risk modeling, and customer analytics.ResponsibilitiesBuild, fine‑tune, and deploy ML models and LLMs for credit scoring, AML, and automation.Implement RAG‑based GenAI applications using internal banking data.Develop scalable data pipelines for training, validation, and real‑time inference.Collaborate with risk, compliance, finance, and business teams for AI solutions.Ensure regulatory compliance and AI governance standards.Implement data security, privacy, and access control mechanisms.Integrate AI models into production using APIs and microservices.Apply prompt engineering and model optimization techniques.Monitor model performance, drift detection, and continuous improvement.Develop explainable AI (XAI) for transparent decision‑making.Optimize cost, latency, and scalability of AI systems.Troubleshoot AI/ML system issues across data and deployment layers.Write efficient Python code using AI frameworks.Follow MLOps best practices (CI/CD, automated deployment).Ensure responsible AI practices (bias, fairness, ethics).Mentor teams and contribute to enterprise AI platforms.Technical SkillsLanguages: PythonAI/ML & GenAI: Machine Learning, Deep Learning, LLMs, Prompt Engineering, Fine‑tuningFrameworks: TensorFlow, PyTorchGenAI Tools: LangChain, LlamaIndexVector DB: Pinecone, FAISSCloud Technologies: AWS, Azure, GCPData Pipelines: ETL/ELT, Real‑time & Batch ProcessingIntegration: APIs, MicroservicesConcepts: RAG Architecture, XAI, Model OptimizationMethodologies: Agile/Scrum, MLOps (CI/CD, Model Versioning, Deployment)Compliance: Banking regulations (SR 11‑7, GDPR), Model Risk ManagementSoft Skills: Strong communication, stakeholder management, and analytical thinkingSalary Range$100,000 - $110,000 per year#J-18808-Ljbffr