We're committed to bringing passion and customer focus to the business.
Key Responsibilities
- Architect and implement RAG pipelines, agentic AI systems, and LLM-driven applications for enterprise use cases.
- Design and integrate prompt engineering, context management, and knowledge-grounding frameworks to optimize LLM performance.
- Collaborate with data, ML, and software engineering teams to build production-grade GenAI microservices and APIs.
- Evaluate and integrate open-source and proprietary LLMs (e.g., OpenAI, Anthropic, Mistral, Llama, Gemini).
- Design data pipelines for unstructured/structured content ingestion, indexing, and vector retrieval using Milvus, PostgreSQL (pgvector), or similar technologies.
- Define and enforce architecture standards, governance, and best practices for scalable GenAI platforms.
- Conduct PoCs, benchmark model performance, and lead solution transitions from prototype to production.
- Contribute to AI strategy, model lifecycle management, and cost optimization initiatives.
