Ritish Bhardwaj

About Ritish Bhardwaj

Backend-focused Software Engineer with 1.5+ years of experience building Python-based systems in telecom environments. Experienced in designing RESTful APIs using FastAPI, implementing repository patterns, managing PostgreSQL persistence layers, and handling transactional workflows. Beyond enterprise systems, I independently designed and implemented a Retrieval-Augmented Generation (RAG) backend integrating embeddings, vector databases, and LLM orchestration to build domain-aware AI solutions. Strong foundation in Data Structures & Algorithms (400+ problems solved) with hands-on experience in API design, database optimization, and modular backend architecture. Currently seeking backend and AI-focused engineering roles in product-driven environments.

Experience

1. Software Engineer

   Amdocs

   Jul 2024 — Present · Gurugram, IN

   Client : Rogers Canada – Designed request/response schema models using Pydantic in FastAPI and implemented structured mapping between API DTOs and PostgreSQL-backed persistence layers, ensuring strong validation and data integrity.– Applied TMF640 Open API principles while designing RESTful endpoints in FastAPI, ensuring correct request modeling, response contracts, and lifecycle state handling in telecom-oriented workflows.– Implemented repository pattern in FastAPI to isolate persistence logic from business services, handling CRUD operations and transactional database sessions.– Developed Python-based automation utilities for Test Data Management (TDM) workflows handling 230+ environment requests monthly, reducing manual provisioning effort by 63%.– Built a SOAP API integration tool to automate user creation across different environments, processing 200+ user operations per month via dynamic XML payload generation.– Designed and developed a Proof-of-Concept GenAI-powered Retrieval-Augmented Generation (RAG) system to centralize telecom Lessons Learned (LL) data across multiple operational domains.– Implemented document chunking, embedding generation (nomic-embed-text), and semantic retrieval using ChromaDB for vector indexing.– Integrated Ollama (qwen2.5) LLM backend with prompt templating and response orchestration for context-aware answer generation.– Performed Root Cause Analysis (RCA) for 50+ production batch failures using Linux logs, Control-M monitoring, and Oracle SQL queries, improving issue resolution time

Education

• Guru Nanak Dev University, Amritsar

  Bachelor of Technology - BTech, Computer Science