- Design and implement AI systems using machine learning, deep learning, NLP, and generative AI.
- Develop LLM-powered applications utilizing prompt engineering, RAG, and structured outputs.
- Build agentic AI solutions capable of planning, reasoning, and tool interaction.
- Create orchestrated multi-agent workflows with robust observability and fallback handling.
- Deploy, monitor, and maintain AI models and agents in production environments.
- Develop data pipelines for ingestion, vector search, and agent context management.
- Define and implement evaluation frameworks for model quality, latency, and safety.
- Optimize AI systems for performance, cost-efficiency, and token usage.
- Apply governance, security, and privacy best practices for responsible AI.
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