Swapnil Sanjay Pawar

About

AI/software engineer with hands-on experience deploying an LLM-powered quiz generation platform for students, integrating Python services with Gemini APIs plus frontend and database components. Emphasizes production-grade reliability through observability, schema validation, async processing, and performance tuning under high concurrency, and has collaborated with product/operators (e.g., at Colombo AI) to translate real-world constraints into scalable technical solutions.

Experience

Education

Key Strengths

• Production deployment of multi-component AI/LLM systems (backend, API integration, frontend, database)
• Designing for reliability with external LLM dependencies (latency mitigation, async workflows, user feedback loops)
• Strong observability/debugging practices (request IDs, stage-level logging, prompt/version tracking, validation outcomes)
• Improving output quality via strict schema validation and sanity checks for educational content
• Systematic root-cause isolation across software/network/resource layers using logging + monitoring
• Scaling under concurrency (queueing, throttling, retries/backoff, resizing based on metrics and load tests)
• Requirements translation with non-technical stakeholders into testable specs and iterative prototypes
• Customer/operator collaboration to convert operational constraints (cost/latency/reliability) into engineering decisions (batching/caching/fallbacks)