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Software Engineer with 1+ years in Python & FastAPI
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Assessing your cultural and operational fit
AI Software Engineer with hands-on experience building scalable APIs and AI-powered systems using Python. Proficient in FastAPI, PostgreSQL, Redis, Docker, LLMs, and AWS. Proven track record designing RAG pipelines, automated data-ingestion systems, and deploying containerized services in production environments.
Greater Noida Institute of Technology (GNIOT)
Bachelor of Technology · Information Technology
August 1, 2020 – June 30, 2024
Infomerica Inc
Software Engineer
September 1, 2025 – Present
Hyderābād, Telangana, India
Infomerica Inc
Software Developer Trainee
December 1, 2024 – August 31, 2025
Hyderābād, Telangana, India
CMS Package Processing & Workflow Agents System
June 1, 2026 – Present
Developed asynchronous REST APIs using FastAPI for workflow orchestration and production backend processing systems. Built an automated CMS package ingestion pipeline to download packages, validate archives, perform OCR-based document extraction, and structure extracted content using LLMs; processed documents with artifacts stored in AWS S3. Designed PostgreSQL schemas to manage package metadata, workflow states, extracted document information, and processing history for reliable pipeline execution. Integrated MCP server endpoints to expose and verify processed package metadata stored in PostgreSQL. Contributed to async-based Agents APIs responsible for orchestrating workflow execution, task routing, and multi-step agent processing pipelines.
Medical Document Intelligence - RAG System
June 1, 2026 – Present
Built a Retrieval-Augmented Generation (RAG) system to answer natural-language queries from medical documents, achieving 85% answer relevance on internal test queries. Implemented a document ingestion pipeline extracting text, tables, and images from PDFs using the Unstructured library, processing 20+ medical documents. Generated and stored embeddings in pgvector, enabling hybrid retrieval using vector similarity and PostgreSQL full-text search. Optimised query latency using Redis caching and asynchronous FastAPI endpoints, cutting average response time from 3s to under 800ms for repeat queries.
AI Chatbot with Memory Architecture
June 1, 2026 – Present
Developed a multi-user AI chatbot backend using FastAPI and LangGraph supporting thread-based conversations and asynchronous request handling. Designed short-term and long-term memory architecture to maintain conversational context, storing message history in PostgreSQL for persistent interactions. Implemented LangGraph-based workflow orchestration to manage conversation state, memory retrieval, and LLM response generation. Secured APIs using JWT authentication with Redis-based token blocklisting and caching to reduce repeated LLM calls and improve response latency. Built scalable chat session management enabling multiple concurrent users with isolated conversation threads.
Introduction to Model Context Protocol -Anthropic
Anthropic
June 1, 2026 – Present
Building with the Claude API - Anthropic
Anthropic
June 1, 2026 – Present
AWS Foundations of Machine Learning and Artificial Intelligence.
Unknown
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's project diversity, including personal and professional projects, showcases initiative and a broad interest in AI/ML applications. Their experience with various technologies (Python, FastAPI, LLMs, Docker, AWS) indicates adaptability. The role alignment with 'Software Engineer' is strong, given their hands-on experience in backend and AI system development. The certifications from Anthropic and AWS further demonstrate a commitment to continuous learning and staying current with industry trends.
Soft Skills & Operational Fit
The candidate demonstrates strong problem-solving skills through bug resolution and system optimization. Their experience mentoring interns suggests good collaboration and communication potential. The focus on building scalable, efficient systems aligns well with operational needs for robust software.