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Manas Rai — Software Engineer · GenAI Engineer

Bengaluru, India · rai.manas12@gmail.com · LinkedIn · GitHub

Software Engineer with ~5 years building production backend systems, the last ~2 focused on Generative AI — Large Language Model (LLM) applications, Retrieval-Augmented Generation (RAG) pipelines, and multi-agent systems — built on an earlier foundation in async Python microservices, distributed data pipelines, and semantic search. Owns systems end-to-end: architecture, backend services, cloud infrastructure, and production launch, including a multi-tenant healthcare RAG platform load-tested for 2,000+ concurrent sessions at sub-second latency. Comfortable operating on either track — core backend/API engineering in Python and FastAPI, or agentic/LLM system design — with hands-on depth in vector databases, prompt engineering, and cloud-native deployment on AWS and Azure. Certified across Anthropic's Claude ecosystem: API development, Model Context Protocol (MCP), and Claude Code.

Skills

  • Backend & Languages: Python, Go (Golang), FastAPI, Flask, Django, REST APIs, Microservices Architecture, WebSockets, Async Programming, SQLAlchemy (ORM), Alembic (DB Migrations), System Design, Software Architecture
  • Generative AI & LLMs: Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, Agentic Architecture, Multi-Agent Orchestration, Prompt Engineering, LangChain, LangGraph, LangSmith, OpenAI API, Anthropic Claude API, Model Context Protocol (MCP), Google Agent Development Kit (ADK), Agent-to-Agent (A2A) Protocol, Embeddings, Vector Databases, NLP, LLM Evaluation, RAGAS, LLM Observability, LLM Cost Monitoring
  • Data Science & ML: pandas, numpy, scikit-learn, Exploratory Data Analysis (EDA), Feature Engineering, Hugging Face (embedding models)
  • Frontend: React, JavaScript, HTML5
  • Databases & Vector Stores: PostgreSQL, MySQL, MongoDB, Neo4j, Snowflake, Aurora, Redis, SQL, NoSQL, Pinecone, pgvector, FAISS, MongoDB Atlas Vector Search
  • Cloud & DevOps: AWS (EC2, RDS, ECS, S3, SQS, Lambda, Bedrock, Cognito), Azure (Azure OpenAI), Docker, Kubernetes, Jenkins, CI/CD, Git, Datadog, MLOps, Cloud Deployment
  • Tools & Practices: Claude Code, VS Code, Jira, GitHub, Agile, Scrum

Experience

Tech Lead · Tricon Infotech Jul 2024 – Present · Bengaluru, India
  • Launched a healthcare chatbot from zero to production by architecting a multi-tenant RAG pipeline on Azure with tenant-isolated vector stores, secure authentication, and data partitioning — directly enabling the product's first paying customers.
  • Engineered an LLM-powered clinical simulation platform (AWS/EKS, multi-provider, real-time text + voice) that role-plays authored patient cases for physician training, with an automated feedback report scoring each trainee's questions and investigations; load-tested for 3,000 concurrent sessions at sub-second response latency.
  • Built a multi-tenant VS Code agent platform with a meta "maker" agent that generates governed agents, skills, hooks, and prompts — interviewing the developer, planning, and checking new instructions against the existing set before implementing.
  • Reduced manual developer workflow time by ~60% by automating multi-step SDLC tasks (code-review scaffolding, test generation, documentation) through agentic orchestration patterns.
  • Shipped a multi-tenant lead-generation data pipeline with SQLAlchemy and AWS Cognito, enforcing per-account data isolation across 5+ client accounts.
  • Built an automated NLP-powered web crawler that extracts and structures institutional data, powering a qualification-matching recommendation engine — cutting 15+ hours/week of manual research.
Solution Leader · Brane Enterprises Oct 2021 – Jul 2024 · Hyderabad, India
  • Promoted 3 times in 3 years (Trainee → Developer → Senior Developer → Solution Leader), the fastest progression in the engineering org at the time.
  • Cut data retrieval time by 75% (4x faster) by implementing semantic search with Neo4j graph traversal and MongoDB vector indexing across 500K+ embeddings and data points.
  • Improved real-time audio transmission stability by 35% by engineering bidirectional WebSocket streaming with adaptive buffering and error recovery for NLP voice applications.
  • Designed and deployed async Python microservices for non-blocking concurrent request handling, increasing API throughput and resolving request-timeout failures seen under production load.
  • Built a FastAPI persistence service with JWT authentication serving as the data backbone for multiple product interfaces, with zero-downtime deployments and CI/CD integration.

Selected projects

  • Healthcare RAG Platform Python · FastAPI · Azure AI Search · Azure OpenAI · Azure AD B2C · Document Intelligence · LangChain · Cosmos DB · RAGAS · Multi-tenant

    A multi-tenant Retrieval-Augmented Generation platform for a healthcare product — tenant-isolated vector stores, secure authentication, and strict data partitioning, taken from zero to production and load-tested for 2,000+ concurrent sessions at sub-second latency.

  • Clinical Simulation Platform Python · Go · AWS · EKS · OpenAI · Anthropic · Realtime voice · WebSockets · PostgreSQL · LIT

    An LLM-powered clinical simulation platform for physician training — prompt-engineered patient personas driven by authored case content, over real-time text and voice, plus an automated feedback report that scores the trainee. Load-tested for 3,000 concurrent sessions at sub-second latency.

  • DevFlow Kit Python · LangGraph · GitHub Actions · Claude Code · Jira

    Multi-agent SDLC automation that turns Jira tickets into production PRs with zero added infrastructure. Refinement, implementation, and Jira-sync agents decompose complex tickets into parallel subtasks and cut the ticket-to-PR cycle from days to hours.

  • RegLens Python · LangGraph · Google ADK · A2A / JSON-RPC · Gemini · Claude · pgvector · FastAPI · RAGAS · Next.js

    Multi-agent regulatory compliance automation. Feed it a regulatory PDF and your control matrix — a compliance research agent extracts every obligation, a gap analyzer checks each against your policies via RAG and scores the risk, and a report generator produces an audit report with a human-in-the-loop approval gate. Includes a drift-detection evaluation harness.

  • CostTracker Python · ClickHouse · PostgreSQL

    Open-source, self-hosted LLM cost tracking SDK. A drop-in instrumentation layer wraps OpenAI, Anthropic, Groq, and Bedrock clients to record usage straight to ClickHouse or PostgreSQL — real-time token metering, per-request cost attribution, and a bundled analytics dashboard.

  • Cloud Waste Hunter Python · FastAPI · scikit-learn · Next.js

    Cloud-agnostic resource monitor with ML-powered waste detection. Flags idle instances, unattached volumes, and stale snapshots across providers in a unified cost-optimization dashboard — then eliminates them safely with dry-run previews, human-in-the-loop approval, and 7-day rollback.

Certifications

  • Building with the Claude API — Anthropic Academy
  • Introduction to Model Context Protocol (MCP) — Anthropic Academy
  • Claude Code in Action — Anthropic Academy

Awards

  • Outstanding Performer Award — Tricon Infotech (Dec 2025). Recognized for delivering 2 end-to-end AI products in a single year.
  • Spot Award — Tricon Infotech. For shipping the healthcare chatbot from architecture to production launch.

Education

B.Tech., Mechanical Engineering · UPTU, Uttar Pradesh, India 2014
Competitive Examination Preparation & Career Transition 2014 – 2021

Full-time preparation for India's UPSC Engineering Services Examination, followed by a self-directed transition into software engineering and applied AI.