Résumé
Applied AI Engineer · Ahmedabad, India
Mubin Attar
Applied AI Engineer with 3+ years in software engineering and a production-AI focus since 2024. I build LLM applications, agentic and RAG systems, predictive ML, and healthcare automation across FastAPI, Next.js, PostgreSQL, and Docker. Four public AI projects document my work in authentication, CI/CD, validation, and task-level evaluation.
Experience
AI/ML Engineer · Sevina Technologies
Ahmedabad · 2024 – present- Build and ship production AI & automation systems for healthcare — end-to-end pipelines (Python, Playwright, Selenium) that extract, validate, and synchronize clinical, resident, and demographic data into SQL Server, with logging, reconciliation, and error recovery.
- Developed an AI clinical decision-support platform that turns CMS MDS assessments into interactive dashboards, compliance findings, and reimbursement insights (HIPPS/PDPM) for skilled-nursing facilities via automated PDF extraction and deterministic, guideline-aligned rules.
- Built Generative AI applications — LLM document-analysis assistants with multi-provider routing (OpenAI, Claude, Gemini), RAG, and validated structured output — plus a FastAPI eligibility-verification service with async batch processing, Dockerized deploys, and CI/CD.
Junior Python Developer · Linescripts Software Pvt Ltd
Pune · 2022 – 2024- Delivered end-to-end web applications — including a Hospital Management System and e-commerce platforms — with Python, Django & DRF, and responsive HTML5/CSS3/JavaScript/Bootstrap frontends.
- Built RESTful APIs and backend services, integrated third-party APIs, and collaborated cross-functionally on requirements, design, and testing.
Featured projects — case studies & source code
Natural-language-to-SQL agent — LangGraph pipeline, schema-aware pgvector retrieval, multi-LLM fallback, and a fail-closed read-only safety layer.
101/139 Spider dev · 18/22 golden-set exact · 4/4 unsafe prompts refused · FastAPI · LangGraph · Next.js · method
Quant backtesting platform with next-bar execution, costs modeled by default, Decimal accounting, and an AI copilot grounded in the backtest results.
Look-ahead canary + cash-conservation tests green · FastAPI · Next.js · TimescaleDB · Redis · method
Sports-betting analytics & ML predictions — +EV best bets, a validated XGBoost model, cross-book arbitrage finder, and a graded, verifiable track record.
65.2% ± 0.8% XGBoost accuracy (5-fold CV) · Django/DRF · FastAPI · Next.js · method
Education
Master of Computer Applications (MCA)
Savitribai Phule University of Pune
2021 · CGPA 8.0