Prototype and integrate LLMs (OpenAI, Azure OpenAI, Anthropic, etc.) into web services, apps, and workflows.
Support the design and development of intelligent chatbots and autonomous agents using cutting-edge GenAI technologies to support content analysis, content gap identification, content summarization and like activities.
Implement and optimize RAG (Retrieval Augmented Generation) systems to provide accurate information retrieval and contextual responses
Write prompt chains, system prompts, and structured outputs (JSON/XML/Markdown) for reliable responses.
Build evaluation harnesses: test sets, metrics, and A/B experiments.
Develop, manage, and deploy intelligent AI agents to include knowledge retrieval (RAG), allowing interaction with external APIs, databases, and applications.
Develop connectors and RAG pipelines.
Use open-source platforms for debugging, testing, and monitoring generative AI applications.
Implement guardrails and safety (content and safety filters, PII scrubbing, hallucination detection, policy enforcement).
Contribute to backend services (Python/TypeScript) and micro-APIs to operationalize AI features.