Role Overview :

Design and deploy enterprise-grade AI solutions (LLMs, RAG, agents) by selecting appropriate models, building data pipelines, and integrating them with cloud platforms (AWS, Azure, GCP). Lead technical strategies, ensure scalability, manage AI security/ hallucinations, and bridge business needs with engineering teams.

Key Responsibilities :

- System Design &
- Architecture: Architect end-to-end Generative AI systems, including retrieval-augmented generation (RAG) and vector data systems.
- Model Selection &
- Tuning: Evaluate and select cutting-edge commercial (e.g., GPT-4) and open-source models, and fine-tune models for domain-specific use cases.
- LLMOps &
- Pipelines: Establish LLMOps standards for model versioning, evaluation, prompt management, and CI/CD, ensuring robust, production-grade AI.
- Integration &
- Security: Integrate AI solutions with existing APIs, applications, and databases while enforcing security, privacy, and guardrails to manage hallucinations and adversarial attacks.




- Strategic Leadership: Collaborate with stakeholders to map business challenges to AI solutions and establish AI governance frameworks.

Tech Stack &

Qualifications :

- Technical Expertise: Deep knowledge of NLP, Python, deep learning frameworks (PyTorch/ TensorFlow), and AI frameworks like LangChain, Autogen, or CrewAI.
- Cloud &
- Data Systems: Extensive hands-on experience with AI services on AWS, Azure, or GCP. Expertise in vector databases (e.g., Pinecone, Milvus, Chroma) and embedding techniques.
- GenAI-Specific Skills: Prompt engineering, RAG architectures, Fine-tuning LLMs, Vector databases.
- Soft Skills: Problem-solving mindset, strategic thinking, and solid communication.
- Qualifications: Bachelor's / Master's in Computer Science, AI, Data Science, or related field; 8 - 15 years in software engineering, ML, or AI roles.

📌 EXL - Assistant Vice President - Generative AI (India)
🏢 EXL Services
📍 India