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# GenAI Engineer

- **Company:** Tata Consultancy Services Limited
- **Location:** Wilmington, DE, United States
- **Salary:** $100,000.0 - $110,000.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Batch Processing, Program Optimization, Continuous Integration, Extract Transform Load (ETL), Data Security, Fraud Prevention and Detection, Python (Programming Language), Machine Learning, Scrum Methodology, Tensorflow, Pytorch, Large Language Models, Prompt Engineering, Deep Learning, Generative AI, AI Platforms, Low Latency, Deployment Automation, Machine Learning Operations, Software Version Control, Data Pipelines, Microservices
- **Published:** June 20, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=cc3d33cc6012689e

## About the Role

Do you have experience in Stakeholder relationship building?

## Description

Design and develop AI/ML and Generative AI solutions for banking use cases including fraud detection, risk modeling, and customer analytics.

 * Build, 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.

 * Languages: Python

 * AI/ML & GenAI: Machine Learning, Deep Learning, LLMs, Prompt Engineering, Fine-tuning

 * Frameworks: TensorFlow, PyTorch

 * GenAI Tools: LangChain, LlamaIndex

 * Vector DB: Pinecone, FAISS

 * Cloud Technologies: AWS / Azure / GCP

 * Data Pipelines: ETL/ELT, Real-time & Batch Processing

 * Integration: APIs, Microservices

 * Concepts: RAG Architecture, XAI, Model Optimization

 * Methodologies: Agile/Scrum, MLOps (CI/CD, Model Versioning, Deployment)

 * Compliance: Banking regulations (SR 11-7, GDPR), Model Risk Management

 * Soft Skills: Strong communication, stakeholder management, and analytical thinking


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