AI Agent Development - Internship

Selected intern's day-to-day responsibilities include:

1. Orchestrate AI agents: Design small agent teams (e.g., writer fact-checker
editor) using frameworks like LangGraph or CrewAI. Define roles, prompts, and
IO contracts, guardrails, and escalation paths.
2. Build & refine RAG pipelines: Chunking strategies, indexing, retrieval
quality, grounding with citations; balance recall/precision for Ayurveda
knowledge.
3. Evaluate & test: Create golden datasets and harnesses for unit/integration
tests; measure quality, latency, cost; prevent regressions via automated
checks.
4. Rapidly iterate architectures: Diagnose failure modes (hallucination,
drift, formatting errors) and adjust prompts, tools, or graph topology until
outputs hit the bar.
5. Instrument & observe: Add tracing/telemetry for runs, token/latency
budgets, and quality dashboards.
6. Collaborate for impact: Translate growth goals into agent flows; ship
internal tools that enable content production, SEO experiments, and campaign
support.
7. (Nice) Wire up tools via MCP: Use the Model Context Protocol (MCP) to
connect agents to internal data/services.