FastAPI backends, LangChain pipelines, React frontends — fintech and AI systems built for production.
About
About
Spent 4+ years across professional engineering roles — most recently as a Full Stack Python Developer at State Street in Toronto, shipping production fintech software in Python, Django, and React for institutional clients.
After State Street in mid-2025, spent six months building deeper expertise in AI agent systems: RAG pipelines, LangGraph multi-agent orchestration, and LLM-integrated backends — then took that work into client engagements via Upwork in early 2026.
Currently building AI-enabled APIs and full-stack products for growth-stage teams, combining reliable Python backends with modern AI toolchains and cloud-native deployment practices.
Based in Ahmedabad, India. Previously worked on-site in Toronto, Ontario. Open to full-time remote roles with North American or global teams.
Experience
Experience
Freelance Software Engineer
- Shipped production-ready FastAPI and Django platforms for 5+ startup clients, taking features from architecture to AWS/GCP deployment across React and Next.js frontends.
- Built AI-enabled workflows using LangChain, LangGraph, and OpenAI APIs — reducing client knowledge-retrieval overhead by 60%+ through automated summarization and semantic search.
- Designed PostgreSQL, MongoDB, and Pinecone-backed systems handling 10k+ daily requests with p95 latency targets under 200ms.
- Standardized Docker-based CI/CD pipelines across all client projects, cutting manual release steps by 50% and improving rollback confidence.
- Maintained a 5-star client rating through consistent milestone delivery, proactive trade-off communication, and production-ready handoffs.
Full Stack Python Developer
- Delivered 15+ full-stack fintech features in Python, Django, and React across 4 distributed engineering teams serving institutional clients globally.
- Built and maintained REST APIs and Python/SQL ETL pipelines processing 500k+ daily records from 3 upstream data sources.
- Optimized 10+ critical SQL queries across SQL Server and MySQL, reducing P95 report-generation latency by ~40% for analyst dashboards.
- Stabilized Kubernetes rollouts and Docker CI/CD pipelines, cutting deployment failures by 30% across staging and production environments.
- Increased test coverage by 25% through structured Pytest suites and static analysis, sustaining predictable Agile sprint cadence.
- Ran ML experiments with PySpark, scikit-learn, and ResNet-based CNNs to improve downstream classification accuracy for operational data models.
Python Developer / Machine Learning Engineer
- Built and deployed 3 production web applications with Django, Flask, React, and MySQL serving automotive and internal business use cases.
- Integrated 5+ third-party REST APIs while coordinating frontend and backend delivery, maintaining stable releases across 8-month delivery cycles.
- Established Pytest coverage from scratch, reducing post-release regressions by 20% across shared application modules.
- Applied Pandas, NumPy, and SciPy pipelines to 50k+ audio sample datasets supporting NLP and computer-vision ML experiments.
- Achieved 90%+ classification accuracy on musical instrument detection using VGGish feature extraction with attention, LSTM, and ConvNeXt neural architectures.
- Benchmarked 4 model variants through systematic cross-validation, establishing reproducible experimentation standards for the ML research workflow.
Education
Education
Conestoga College
Post Graduate Degree — Web Development
Gandhinagar Institute of Technology (GTU)
Bachelor of Engineering — Computer Science
Skills
Skills
Certifications
Certifications
Complete Data Science, Machine Learning, DL, NLP Bootcamp
Udemy · 2025
Python with Machine Learning
Softvan Pvt Ltd | A Sahana System Group Company · 2020
Certificate available on request