LLM Integration & Prompt Engineering
✓ Design and integrate LLM-powered features using OpenAI, Anthropic Claude, and open-source model APIs
✓ Craft, iterate, and systematically evaluate prompts for accuracy, safety, and cost-efficiency
✓ Implement structured output parsing, function calling, and tool-use workflows
Agentic Pipeline Development
✓ Build multi-step agentic workflows using frameworks such as Adk,LangChain, LlamaIndex, CrewAI, or AutoGen
✓ Architect multi-agent systems with clear role separation, task delegation, and coordination logic
✓ Implement memory systems (short-term, long-term, episodic) to enable persistent agent behavior
RAG & Knowledge Systems
✓ Design and maintain Retrieval-Augmented Generation (RAG) pipelines from ingestion to generation
✓ Work with vector databases (Pinecone, Weaviate, Chroma, pgvector) for semantic search and retrieval
✓ Optimize chunking strategies, embedding models, and re-ranking to maximize retrieval quality
Evaluation & Observability
✓ Define and track metrics for LLM output quality, latency, cost, and reliability
✓ Set up evaluation frameworks (RAGAS, LangSmith, custom harnesses) to benchmark system performance
✓ Monitor production AI systems and debug regressions or hallucinations proactively
