onsite
Principal Architect AI Data Engineer - EXL Service
Data Engineer
Lead the design and implementation of enterprise‑grade GenAI and agentic solutions, defining reference architectures, RAG pipelines, and best practices while ensuring scalability, reliability, and cost‑effective performance.
About the role
Key Responsibilities
- Design and govern enterprise‑scale Generative AI and agentic architectures, including single‑agent, multi‑agent, and tool‑driven systems.
- Define reference architectures, reusable frameworks, and best practices for LLM‑based applications across the organization.
- Architect end‑to‑end Retrieval‑Augmented Generation pipelines covering data ingestion, chunking, embedding creation, vector search, orchestration, and response synthesis.
- Ensure scalability, reliability, performance, and cost optimisation of GenAI platforms in production.
- Provide hands‑on technical leadership for prompt engineering, model fine‑tuning, and LLM integration while mentoring engineering teams.
Requirements
- 10+ years of experience in data engineering, AI/ML, and cloud architecture, with a strong focus on large language models.
- Proficiency in Python and modern data‑processing frameworks (e.g., Spark, Flink) for building high‑throughput pipelines.
- Deep knowledge of Retrieval‑Augmented Generation, vector databases, and prompt engineering techniques.
- Hands‑on experience designing and operating cloud‑native solutions (AWS, Azure, or GCP) at scale.
- Proven ability to lead cross‑functional teams, define technical standards, and drive architectural decisions in complex, enterprise environments.