Agentic AI & Multi-Agent Architecture
- Design and implement agent-based and multi-agent systems using frameworks such as CrewAI, LangGraph, AutoGen, and LangChain.
- Build autonomous agents capable of planning, reasoning, tool usage, and long-running task execution
- Integrate LLMs with tools, APIs, memory stores, vector databases, and RAG pipelines
LLM Development & Optimization
- Fine-tune and optimize foundation models (e.g., Mistral, Gemini Flash, OpenAI models, AWS Bedrock)
- Develop advanced prompt strategies and control loops for agent reasoning
- Build NLP pipelines for summarization, classification, QA, and text generation
Production Deployment & Scalability
- Deploy AI services and agent workflows to production environments.
- Optimize solutions for latency, cost, memory usage, and scalability
- Collaborate with DevOps and platform teams on CI/CD, monitoring, and reliability
Evaluation, Safety & Reliability
- Implement evaluation frameworks for LLM and agent performance
- Ensure robustness, observability, and responsible AI deployment
- Apply AI safety, ethical AI, and governance best practices
Cross-Functional Collaboration
- Work closely with product, research, data engineering, and software teams
- Translate business requirements into scalable AI solutions
- Mentor junior engineers and contribute to design reviews
Documentation & Knowledge Sharing
- Maintain detailed technical documentation
- Communicate system design, trade-offs, and outcomes to stakeholders
