Vetted Django Professionals

“Backend engineer who has owned end-to-end delivery of Python/FastAPI microservices for real-time data processing and alerting, including performance tuning (Postgres optimization, caching, async processing). Strong DevOps/GitOps background: Docker + Kubernetes deployments with GitHub Actions CI/CD and ArgoCD-driven GitOps, plus experience supporting phased on-prem to AWS migrations and building Kafka-based streaming pipelines.”

“JavaScript full-stack engineer with experience at EY building secure, cloud-ready React/Node.js applications on AWS and currently at startup Juego Juegos owning the AWS backend and CI/CD via AWS Amplify. Demonstrated impact through performance tuning of a React analytics dashboard (reduced initial load time ~20%) and resolving real payment failures by debugging Stripe 3DS flows and updating AWS Lambda plus frontend error handling.”

“Backend engineer with cloud-native Python/Flask experience building high-throughput financial platforms (loan origination intelligent document processing and real-time fraud detection). Has scaled microservices on AKS with event-driven Azure messaging, delivered measurable performance gains (e.g., 700ms→180ms query latency; ~40% API improvements), and implemented strong security controls (OAuth2/JWT, Azure AD RBAC, audit logging, AES-256/TLS) for sensitive regulated data.”

“Built and launched a verified listings system for Burrow (student subleasing) after interviewing ~50 students about scam/fake listing concerns; chose a lightweight .edu-based verification approach to ship fast and then iterated with badges and clearer details, reducing churn from 15% to 7%. Also ran an LLM A/B test for auto-generating listing descriptions and improved trust/accuracy by updating prompts to prevent hallucinated details.”

“Full-stack engineer in an early-stage startup who built an EV charger monitoring and payments dashboard from scratch, owning UI/UX (Figma), React frontend, Node/Postgres APIs, and production deployment/ops (Firebase + AWS). Demonstrated measurable impact (40% fewer reconciliation errors) and strong reliability chops through multi-source energy/payment ingestion, idempotent pipelines, and CloudWatch-driven incident resolution.”

“Backend/data engineer focused on production Python and AWS: built FastAPI REST services and a containerized ECS Fargate + Lambda architecture deployed via Terraform/CI-CD. Strong in data engineering (Glue/S3/Parquet/RDS) and operational reliability (CloudWatch/SNS, retries, schema-evolution handling), with experience modernizing legacy SAS reporting into Python microservices using feature flags and parity validation.”

“Software engineer who has shipped both core web platform features (secure user authentication/profile management) and production LLM systems. Built an internal documentation knowledge assistant using a full RAG pipeline (OpenAI embeddings, vector DB, semantic search, reranking) with evaluation loops and a scalable document-ingestion pipeline for PDFs/FAQs, iterating based on metrics and user feedback.”

“LLM/RAG practitioner building clinician-facing AI search and Q&A inside EHR workflows, focused on trust, latency, and safety (grounded answers with citations, PHI controls, encryption/audit logs). Demonstrated real-time incident response for production LLM systems (e.g., fixing a metadata-filter deployment regression to prevent irrelevant results/cross-patient leakage) and strong demo/enablement skills for mixed technical and clinical stakeholders; also shipped a multi-model RAG tool at OrbeX Labs with upload/search/audit features for day-to-day adoption.”

“ML/AI engineer who built and productionized an NLP system at PurevisitX, orchestrating end-to-end ML workflows with Airflow (S3 ingestion through auto-retraining) and optimizing for drift and low-latency inference. Also partnered with Citibank risk teams on a fraud detection model, translating results via dashboards and iterating thresholds based on stakeholder feedback.”

“Built an AI-powered loan automation dashboard using React and open-source JavaScript libraries, with hands-on experience improving real-world performance by reducing re-renders and optimizing/caching multiple API calls. Also produced developer-friendly API documentation for a voice assistant project, helping teammates integrate features faster with fewer errors.”

“Product-focused full-stack engineer (Spring Boot/Django + React/TypeScript) with deep experience building multi-tenant, enterprise workflow and supply-chain/order-tracking systems. Owned an end-to-end Workflow SLA Breach Prediction & Alerting feature integrating Azure ML for a cloud workflow platform used by ~10,000 enterprise users, and has hands-on AWS operations experience resolving real production latency/scaling incidents via query optimization and Redis caching.”

“Software engineer who built and open-sourced reusable React/Node.js modules (chat, auth, caching) from an AI education platform, emphasizing intuitive APIs and strong documentation. At TCS, improved a healthcare scheduling platform by diagnosing SQL/server bottlenecks and redesigning database + caching, cutting appointment load times by ~40% and reducing support complaints.”

“Healthcare AI/ML engineer with Epic experience who built and deployed a HIPAA-compliant GPT-4 RAG clinical assistant over large medical document sets, emphasizing privacy controls and low-latency performance. Also automated end-to-end retraining and deployment of patient risk models using orchestration/CI-CD (Jenkins, SageMaker, MLflow), cutting deployment time from hours to minutes while improving reliability.”

“Application-focused full-stack engineer in the clinical/health domain who shipped an LLM-powered clinical note summarization workflow end-to-end (FastAPI + Postgres + Kafka workers + React/TypeScript UI) with strong attention to security, auditability, and clinician trust. Has hands-on AWS/EKS operations experience and has resolved real production latency/scaling issues through async processing, query/index tuning, caching, and horizontal scaling.”

“Full-stack engineer with strong ownership in fast-moving environments: designed and shipped a pre-order/campaign inventory system (NestJS + Strapi + Datadog) that freed 34% warehouse space and reduced stock risk to ~5.7%. Also built rapid, high-impact logistics features (Spot Sales) that drove last-mile cost to ~0 in ~40 days, and has hands-on AWS/Terraform/CI-CD experience including deploying a global RAG system with Pinecone, Datadog, and PagerDuty.”

“Full-stack engineer with healthcare and fintech experience who has owned production features end-to-end—most notably an AI assistant clinical risk summary tool on AWS (FastAPI/Lambda + React/TypeScript) that cut analyst review time ~40%. Strong in performance tuning for large datasets (S3/Athena), production ops/observability (CloudWatch, CI/CD, env separation), and building reliable ETL/integrations with idempotency and retries.”

“Has worked at a startup within an incubator program and is a certified mentor with a startup mentorship non-profit focused on early-stage/pre-funded companies. Not currently seeking to found a company or take equity-only roles, but open to working at very early-stage companies (pre-launch/pre-revenue/pre-funded).”

“Founding engineer who built a multi-tenant AWS backend from scratch focused on ultra-fast, configuration-driven client onboarding and low operational cost. Automated tenant provisioning/deployments with Terraform + GitHub Actions (new client infra in ~13 minutes) and scaled to 62 production clients handling ~75k requests/day without a major rewrite. Hands-on with migrations (DynamoDB->MongoDB), reliability/observability, and performance tuning (indexes, Redis, queueing, connection management).”

“Backend engineer with hands-on experience scaling a CVE processing platform by re-architecting it into a Kafka-based distributed system, boosting throughput to 200k+ records/min while designing for HA, deduplication, and fault tolerance. Also led a Flyway-driven migration affecting 15M+ records with staged dev→stage→prod rollout, and has implemented production security patterns (Auth0, OAuth2/HTTPS, AWS IAM RBAC) including least-privilege hardening.”

“Backend/data engineer with production experience building real-time sensor telemetry platforms: FastAPI + PostgreSQL services with strong observability, plus AWS serverless and Glue-based ETL into Redshift. Has modernized legacy SAS pipelines into Python microservices and delivered measurable performance wins (Postgres query latency cut to <1 minute and ~60% DB CPU reduction) while owning incident response and reliability improvements.”

“Built and deployed a production LLM/RAG clinical document understanding and summarization system for healthcare, focused on reducing manual review time while meeting strict accuracy, latency, and compliance needs. Demonstrates strong MLOps/orchestration depth (Airflow, Kubernetes, Azure ML Pipelines) and a rigorous approach to hallucination mitigation through layered, source-grounded safeguards and stakeholder-driven requirements with physicians/compliance teams.”

“Software engineer and University of Chicago graduate teaching assistant who built a full-stack internal analytics dashboard (React/TypeScript + Node/Express) and worked in RabbitMQ-based microservices with Prometheus/Grafana observability. Also created an AI-powered ERD diagram generator (React + MermaidJS + OpenAI) adopted by students to save hours on database assignments, using validation loops to ensure valid Mermaid output.”

“Python backend engineer who owned an end-to-end Django/DRF authentication and account-management module (JWT, RBAC, email verification) and optimized token validation performance. Has hands-on Kubernetes + Helm delivery with GitOps via ArgoCD (multi-environment app-of-apps, drift detection/rollback) and has supported a cloud-to-on-prem migration using staged testing and phased cutover. Also built and scaled a Kafka-based real-time user activity tracking pipeline with reliability and backpressure controls.”