onsite
AI Data Engineer Architect - EXL Service
Data Engineer
Architect AI Data Engineer leading end‑to‑end design of enterprise Generative AI platforms, building scalable agentic systems, and defining reference architectures for RAG, fine‑tuning, and hybrid LLM solutions.
About the role
Key Responsibilities
- Define and own the full architecture for enterprise Generative AI platforms, including data pipelines, model serving, and monitoring.
- Design scalable agentic systems—single‑agent, multi‑agent, and orchestration frameworks—supporting tool calling, function orchestration, and stateful memoization.
- Create and maintain reference architectures, design patterns, and reusable frameworks for Retrieval‑Augmented Generation, fine‑tuning, and hybrid LLM approaches.
- Evaluate emerging technologies (LLMs, vector databases, orchestration tools) and recommend optimal solutions aligned with business goals.
- Collaborate with data engineering, ML, and product teams to ensure seamless integration of AI components into production environments.
Requirements
- 5+ years of experience in AI/ML solution architecture, with a focus on large language models and Generative AI.
- Strong proficiency in Python and experience building data pipelines, model APIs, and orchestration workflows.
- Deep knowledge of Retrieval‑Augmented Generation techniques, vector search engines (e.g., Pinecone, Milvus), and LLM fine‑tuning or hybrid strategies.
- Hands‑on experience with cloud platforms (AWS, Azure, or GCP) and designing scalable, secure AI services.
- Proven ability to lead technical teams, make architecture decisions, and communicate complex concepts to stakeholders.