Role Summary
DXC Technology is hiring an experienced Generative AI Engineer across its major technology hubs in India. In this role, you will design, develop, and deploy cutting-edge AI, ML, and Generative AI solutions—including RAG-based applications, AI Agents, and Copilots. You will integrate Azure OpenAI and open-source LLM frameworks with enterprise data sources, enforce Responsible AI standards, and optimize end-to-end MLOps deployment pipelines.
Key Responsibilities
- GenAI Application Development: Design, build, and deploy enterprise AI solutions, including conversational AI, copilots, autonomous AI agents, and RAG architectures.
- Framework & Model Orchestration: Develop and fine-tune AI workflows using LangChain, LlamaIndex, Hugging Face, and Azure OpenAI / Azure AI Foundry.
- Vector Database Integration: Implement and optimize high-throughput vector store indexes using FAISS, Pinecone, or ChromaDB for efficient semantic document retrieval.
- Integration & MLOps: Connect AI microservices with enterprise backend systems; manage containerized deployments using Docker, Kubernetes, Git, and CI/CD MLOps pipelines.
- Performance & Compliance: Monitor model latency, evaluate output quality, troubleshoot production issues, and maintain strict adherence to data security and Responsible AI guidelines.
Key Qualifications
- Experience: 5+ years of hands-on experience in AI/ML, Generative AI, software development, or data engineering.
- Core GenAI Stack: Deep technical experience with LLMs, RAG patterns, Prompt Engineering, LangChain, LlamaIndex, and Hugging Face.
- Cloud & Vector Search: Expertise in Azure OpenAI, Azure Machine Learning, and Vector DBs (Pinecone, FAISS, ChromaDB).
- Software Engineering: Strong coding proficiency in Python, REST API development, SQL, and microservice architectures.
- DevOps & MLOps: Working knowledge of Docker, Kubernetes, Git, CI/CD pipelines, and MLOps deployment lifecycle.
About DXC Technology
DXC Technology helps global companies run their mission-critical systems and operations while modernizing IT, optimizing data architectures, and ensuring security and scalability across public, private, and hybrid clouds.