6+ years of experience as a Senior Python Developer and Generative AI Engineer, building scalable full-stack applications and production-grade AI systems across finance, media, healthcare, and enterprise tech.
Experience
2026 — Now
2026 — Now
• Building Python and Django REST APIs to support GenAI-powered internal tools, focusing on reducing API response latency across critical business endpoints.
• Contributing to LangChain-based LLM pipelines integrated with vector databases and FastAPI for financial reporting workflows.
• Supporting cloud-native deployments on AWS using Docker and Kubernetes, with monitoring via CloudWatch and for LLM observability.
• Implementing prompt engineering strategies including chain-of-thought reasoning and few-shot learning to optimize token usage and output quality.
• Assisted in enhancing existing LangChain-based LLM pipelines by fine-tuning prompts and improving retrieval logic, leading to better response relevance in financial reporting use cases.
• Supported debugging and performance optimization of Django and FastAPI services, identifying bottlenecks and contributing to reduced API latency across key endpoints.
• Collaborated with cross-functional teams to test and validate GenAI outputs, ensuring alignment with business requirements and improving overall reliability of AI-driven workflows.
2024 — 2025
New York, NY
• Designed and implemented scalable backend using RESTful APIs in Python (Django) to support high-volume, low-latency retail data workflows such as orders, events, and customer interactions.
• Built and exposed Node.js-based REST APIs to enable seamless integration between frontend applications and backend services for real-time data exchange.
• Developed API-driven services for ingesting, validating, and persisting transactional and behavioral data into MongoDB, PostgreSQL, and DynamoDB
Built and deployed Generative AI (GenAI) integrations leveraging modern frameworks and APIs to support automation, content generation, and NLP-driven workflows.
Developed high-performance RESTful APIs and microservices to serve AI/ML models and GenAI functionalities in production environments.
Engineered data processing and feature pipelines to support machine learning use cases, ensuring data quality, reliability, and scalability.
Collaborated with cross-functional teams to integrate AI/ML and GenAI capabilities into business applications, enhancing user experience and system intelligence.
Deployed cloud-native AI services using containerization, CI/CD pipelines, and DevOps best practices, improving system resilience and release efficiency.
Managed the full software development lifecycle (SDLC) from concept to deployment, utilizing Git for version control and implementing CI/CD pipelines to automate testing and release processes.
Optimized application performance by profiling Python code and database queries, resulting in a $30\%$ improvement in API response times for critical business functions.
2022 — 2024
2022 — 2024
North Carolina, United States
• Implemented automated unit, integration, and end-to-end tests using frameworks like Pytest and Django's built-in testing tools, leading to a 45% reduction in post-release bugs.
• Successfully containerized application components using Docker for development and staging
environments, streamlining the onboarding process for new team members.
• Built AI chatbots using GPT-4. LangChain, and vector databases to automate customer support workflows, reducing ticket volume by 6o% while maintaining high satisfaction scores.
• Created internal Al assistants using LangChain agents and LLMs to automate code, documentation, and knowledge retrieval tasks, increasing developer productivity by 30%
• Designed and deployed LLM-powered applications using OpenAl GPT-4› LLaMA, and Mistral with LangChain for orchestration, memory, and tool calling, reducing manual research and analysis effort by 60%
• Built Retrieval-Augmented Generation (RAG) systems using LangChain retrievers,
FAISS/Pinecone/ChromaDB, and Hugging Face embeddings, improving response accuracy and
factual grounding by 42%
2022 — 2022
2022 — 2022
Campbell, CA
• Developed Python-based ETL pipelines to ingest, cleanse, and transform clinical trial datasets from HL7 FHIR and EDC systems, processing 500,000+ patient records with 99.8% data accuracy for downstream analytics.
• Built RESTful microservices using FastAPI and Flask to serve AI-driven insights for clinical data
management, reducing manual data review cycles by 35% for life sciences clients.
• Assisted in designing NLP modules using Hugging Face Transformers and spaCy for automated extraction of adverse events and medical entities from unstructured clinical narratives, improving annotation throughput by 50%.
• Developed responsive front-end dashboards using React, Redux, and Material UI to visualize patient cohort analytics and trial metrics, enabling real-time decision-making for clinical operations teams.
• Integrated backend APIs with PostgreSQL and MongoDB databases using SQLAlchemy ORM and Celery task queues, ensuring reliable asynchronous data processing for high-volume healthcare data workflows.
• Collaborated on HIPAA-compliant cloud deployments on AWS using S3, Lambda, and CloudWatch, ensuring secure handling of protected health information (PHI) across all development and staging environments.
• Participated in Agile sprint ceremonies and peer code reviews, refactoring legacy Python scripts into modular, well-documented packages, improving code maintainability and reducing technical debt by 20%.
2020 — 2021
2020 — 2021
India
• Developed REST API consumers using Python GET and POST methods, validated with Postman, reducing integration defects by 30% during sprint cycles.
• Built and maintained data parsing modules to process CSV, XML, and JSON from REST services, automating ingestion workflows and saving 10+ hours of manual effort weekly.
• Designed interactive web-based solutions using Python, Django Forms, HTML5, and JavaScript, enabling real-time data collection for 20,000+ online users.
• Wrote Python modules to extract and load asset data from MySQL source databases, reducing manual data migration effort by 100% for 3 legacy system integrations.
• Participated in full Agile/Scrum ceremonies including daily stand-ups, sprint planning, and retrospectives, contributing to on-time delivery across 10 consecutive sprint cycles.
Education
University of Mumbai