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Chaitanya Kalagara
Mid-level Machine Learning Engineer specializing in LLMs, GenAI, and Computer Vision
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About
LLM/agent engineer who built a production multi-agent research automation system using LangGraph (planner, retriever with FAISS, supervisor, evaluator) with structured outputs and citation tracking for traceable reports. Emphasizes reliability and operations—LangSmith-based observability, multi-level testing, hallucination mitigation, and latency/cost controls—plus prior experience as a Computer Vision Software Engineer at Deepsight AI Labs working directly with non-technical customers.
Experience
Education
Key Strengths
- Built and deployed an LLM multi-agent research automation system to production
- Strong agent orchestration design (planner/retriever/supervisor/evaluator roles) with LangGraph
- Reliability-focused engineering: strict schemas, fallbacks/retries, multi-level testing (unit/integration/failure cases)
- Grounding and trust features: explicit citation tracking and completeness/consistency evaluation
- Practical mitigation of hallucinations and unsupported claims via iterative prompting and grounding to retrieved sources
- Operational excellence for LLM systems: observability/debugging with LangSmith, plus latency and cost optimization (caching, pruning steps, limiting LLM calls)
- Effective collaboration with non-technical stakeholders; able to explain and align on the right ML metrics (precision vs accuracy)
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