Backend and AI engineering
Backend systems
Product problem to API, schema, migration, tests, deploy. At Adeptmind I own the GenAI QA evaluation platform this way, not ticket by ticket.
Python and TypeScript
Python (FastAPI, Django, SQLAlchemy) daily; TypeScript/JavaScript (Node.js, React) for 2 years across services and frontends.
Async and event-driven systems
Celery queues, WebSocket streaming, scheduled jobs, retries and idempotent workers in production.
LLM applications
Tool calling, structured outputs, RAG, and grounding against real data - shipped and maintained for 3 years with LangChain, LiteLLM, and Mirascope.
Production impact
QA coverage
8% to 100% - automated customer call auditing with a GenAI evaluation platform.
Infrastructure cost
40%+ reduction through backend and cloud optimization.
Latency
10% end-to-end cut in low-latency, event-driven AI workflows.
Experience and education
Software Engineer, Adeptmind
January 2023 - present. Building agentic QA evaluation with LLM orchestration, Django models, PostgreSQL, Celery, and real-time streaming.
Education
B.E. in Electronics and Communication Engineering, NSUT Delhi (2018-2022).
Tools and technologies
Backend
Python, FastAPI, Django, Node.js, PostgreSQL, Neo4j, Redis
AI
LangChain, LiteLLM, Mirascope, RAG pipelines, vector databases, LLM evaluation
Infrastructure
Docker, Kubernetes, AWS, Celery, WebSockets
Frontend
React, JavaScript, TypeScript