Vetted FastAPI Professionals

Ramya Jonnala

Screened

Principal/GenAI Engineer specializing in LLMs, RAG, and MLOps

Plano, TX9y exp

“Built a production AI-powered university marking system that automates question generation and grading from PDF course materials using a RAG pipeline (S3 + Pinecone) orchestrated with LangChain/LangGraph and deployed on AWS ECS via Docker/ECR and GitHub Actions CI/CD. Addressed a key real-world LLM challenge—grading consistency—by implementing rubric-based scoring, retrieval re-ranking, and standardized context summarization, validated against human instructors.”

HarshaVardhanRao Vemuganti

Screened

Junior AI/ML Engineer specializing in Generative and Agentic AI

Lafayette, Louisiana4y exp

“Built and deployed a production-grade LLM agent for credit management and accounts receivable automation, integrating ERP/MySQL data via a RAG pipeline and exposing services through FastAPI with Pydantic-validated outputs on AWS Bedrock. Emphasizes reliability and compliance for financial operations using schema validation and human-in-the-loop review, reporting ~32% reduction in manual work and ~41% improvement in response time/reliability.”

Zaid Kamil

Screened

Mid-level XR Software Engineer specializing in real-time AR/VR digital twins

Los Angeles, CA8y exp

“Built and owned an end-to-end real-time IoT telemetry backend that powers a digital twin experience on a Meta Quest headset, integrating Cisco LoRaWAN sensors and external REST data sources. Migrated from Azure Functions to a FastAPI service to overcome firewall constraints, add caching/fallback reliability, and significantly reduce operating cost while improving performance and evolvability.”

Tim Kwok

Screened

Senior DevOps Engineer specializing in multi-region AWS/GCP cloud infrastructure

United States8y exp

“Backend/data engineer with strong AWS production experience spanning FastAPI microservices and large-scale data pipelines. Has delivered containerized Python services on EKS with Terraform/Helm/GitHub Actions, implemented robust auth/secrets practices, and owned ETL reliability (Glue/S3/Redshift) including incident response and idempotent reruns. Demonstrated SQL tuning on 50M-record ETL workloads to remove SLA misses and improve reliability.”

Suma Mallu

Screened

Intern Full-Stack Software Engineer specializing in UI/UX and AI-integrated web apps

Remote1y exp

“Built and owned Python backend APIs for real-time educational dashboards at ASU’s Machine Learning lab, improving responsiveness by cutting latency ~35% through caching, batching, and profiling-driven optimizations. Has hands-on experience containerizing Node.js/Python services and running GitOps-style CI/CD with GitHub Actions, plus supporting smaller infrastructure transitions with reproducible, portable configs.”

Jeevan Hebbal Manjunath

Screened

Junior Robotics & Machine Learning Engineer specializing in autonomous systems

Tempe, AZ2y exp

“Robotics engineer leading development of a Physical Reservoir Computing controller for a pneumatic soft robotic arm, owning everything from automated data collection and leak-testing automation to hardware design/manufacturing and cross-lab integration with Virginia Tech. Built ROS 2/DDS-based multi-robot systems integrating OptiTrack, a lab quadruped, and a UR5e, and pairs simulation (Gazebo/MuJoCo) + PPO RL training with production-ready tooling (Docker, CI/CD, Flask dashboards, RAG chatbot portfolio).”

ROHITH DAMARLA

Screened

Mid-level Backend Engineer specializing in high-scale systems and LLM pipelines

Syracuse, NY6y exp

“Open-source-focused TypeScript/JavaScript engineer who built a lightweight Node.js utility library to standardize LLM-agent message formatting, tool invocation, and safe schema-validated JSON outputs. Emphasizes composable abstractions, real-world performance profiling/benchmarks, and strong community feedback loops (GitHub issues, structured errors, logging hooks). Also did research at Syracuse University on converting natural language into structured JSON with validation layers.”

Tharun Chowdary Malepati

Screened

Mid-level AI/ML Engineer specializing in GenAI, NLP, and production MLOps

5y exp

“AI/LLM engineer who built and deployed a production healthcare RAG chatbot ("DoctorBot") with strict medical safety guardrails, an 85% confidence-gated verification layer, and latency optimizations that cut responses from ~8s to ~2–3s. Also worked on finflow.ai to generate finance/banking test cases from BRDs, collaborating closely with non-technical domain stakeholders, and has hands-on orchestration experience with LangChain/LangGraph and agentic evaluation/monitoring practices.”

“AI/ML engineer with hands-on experience owning production deployments from discovery through post-launch stabilization, including real-time computer vision/OCR systems and LLM-powered RAG workflows. Stands out for translating messy customer workflows into reliable backend services, debugging non-deterministic retrieval issues, and hardening AI systems with validation, monitoring, and human-review fallbacks.”

“Full-stack engineer who has owned both institutional and personal products end-to-end, including Rutgers' myCommunity platform used by 70,000+ students. Particularly strong in production systems, data synchronization, authentication, and third-party API integrations, with a pragmatic approach to shipping, observability, and UI modernization.”

“AI/ML engineer with 9+ years of experience building production recommendation and LLM systems end-to-end, from experimentation through deployment, monitoring, and retraining. Stands out for combining strong MLOps discipline with practical GenAI/RAG implementation, including measurable impact such as ~25% higher engagement on an e-commerce recommender and nearly 30% faster knowledge retrieval from internal documents.”

“Full-stack JavaScript engineer with hands-on ownership of a retail loyalty platform spanning Next.js on Vercel and NestJS microservices on Azure. Stands out for designing complex real-time and event-driven flows, including Bluetooth-connected React Native work, shared TypeScript contracts across frontend/backend, and production reliability patterns like webhooks, revalidation, logging, and retry Cron jobs.”

“Full-stack and AI product engineer with strong accessibility and voice-interface experience in senior living, building systems for older adults where trust and usability are critical. Has shipped React/TypeScript and .NET MAUI products, productionized Azure OpenAI features, built RAG-based research tools, and improved both product outcomes and technical performance with measurable impact.”

“Master's student who built and owned a recruiter-focused full-stack dashboard with real-time updates, large candidate datasets, and performance-sensitive React UI workflows. Stands out for practical front-end optimization work using Chrome DevTools, CSS/rendering fixes, and TypeScript to improve speed, usability, and maintainability.”

“Early-career frontend/full-stack engineer with internship experience at EventEase, where they built a live scoring and tournament-operations platform for charity golf events. They stand out for owning complex multi-user browser UIs, making thoughtful architecture trade-offs, and translating real user feedback into features like responsive admin tools, moderated photo sharing, and team/organizer chat.”

Faisal Hayat

Screened

Senior Python Full-Stack Engineer specializing in AI-powered backend systems

Lahore, Pakistan6y exp

“Backend-leaning full-stack engineer with startup experience building AI-powered products and ERP/SaaS platforms. They’ve delivered Python/FastAPI/Django and React systems on AWS, including an AI document processing platform and business workflow tools used by thousands of users, with strong hands-on depth in database optimization and production operations.”

“Senior full-stack engineer with 7+ years of Python-centric experience who has worked in lean startup environments and personally drove backend architecture for a data-intensive B2B analytics platform. Stands out for navigating ambiguous, fast-changing requirements while improving scalability and performance through Redis, Celery, RabbitMQ, and PostgreSQL optimization.”

Aditya Niture

Screened

Mid-level Full-Stack Software Engineer specializing in AI-augmented web and mobile systems

Chicago, IL4y exp

“Builder-oriented engineer who has shipped production systems across fintech-style payments, mental health recommendations, industrial oil-and-gas analytics, and AI-assisted client discovery. Stands out for combining deep backend reliability practices with founder-facing product scoping, and reports using Claude-based internal tooling to increase delivery capacity by 40% and handle eight concurrent projects.”

“Built an AI GTM Copilot that consolidated 5+ sales tools into a single browser-based workflow for sales teams, combining LLMs, data enrichment, and outreach automation. Brings a rare blend of ML, backend, and front-end experience, with concrete wins in performance optimization, workflow design, and measurable UX improvements.”

“Early-career full-stack developer who has built and deployed learning projects including a school system dashboard with role-based access and a Node/Express message board, then applied that experience to a real restaurant analytics dashboard in development. Uses AI-assisted tools like Cursor to accelerate coding while manually reviewing outputs, and has hands-on experience debugging frontend/backend issues and validating API inputs.”

“Built a production-grade clinical and insurance document AI system in a HIPAA/PHI-regulated environment, taking it from experimentation through Azure deployment, monitoring, and iterative improvement. Stands out for translating RAG/LLM research into reliable microservices with strong safety controls, drift monitoring, and human-in-the-loop workflows that cut manual review time by 60-70%.”

Emma Choudhary

Screened

Senior Full-Stack Software Engineer specializing in Python, Django, and Generative AI

United States6y exp

“Backend/data engineer with hands-on production experience building partner-facing Python APIs (FastAPI, Celery, Postgres/Redis) and AWS serverless data platforms (Lambda, SQS, Step Functions, Glue). Emphasizes reliability and governance—JWT tenant-scoped auth, secrets/config hygiene, data-quality quarantine, and incident ownership—plus measurable SQL tuning that eliminated timeouts and stabilized reporting workloads.”

“ML/AI engineer with hands-on experience building healthcare and fraud-detection systems from experimentation through deployment, monitoring, and retraining. Stands out for combining real-time IoT pipelines, cloud-native MLOps, and GenAI/RAG in regulated healthcare settings, with reported impact including reduced emergency response times and a 25% reduction in manual diagnosis time.”

“VR multiplayer Unity developer who implemented high-impact interaction systems (notably a math-driven, physics-aware door system with audio occlusion and culling) and designed/built a fully custom cross-platform multiplayer stack from scratch using KCP, WebSockets, WebRTC, and MemoryPack—plus recording, NPC support, and backward-compatible client modes for an educational/learning platform.”