Vetted Python Professionals

“Backend-focused engineer with experience owning a production e-commerce platform end-to-end (TypeScript/Node/Express, React, MongoDB, Redis) including RBAC and contract-based API development. Also worked at Infosys on a large healthcare management system built with Spring Boot microservices, using Kafka for messaging/retries, circuit breakers for resilience, and OpenTelemetry/Swagger for observability and API documentation.”

“Backend/data platform engineer who owned a FastAPI + Kafka microservice in Verizon’s billing pipeline, handling high-volume usage ingestion/validation/enrichment with strong observability and CI/CD on AWS EKS. Demonstrated measurable performance gains (latency down to ~120–150ms; Kafka throughput +30–40%; DB CPU -25%) and led an on-prem ETL-to-AWS migration using Terraform, parallel validation, and phased cutover with zero downtime.”

“At onedata, built and deployed an LLM-powered, multi-agent analytics platform on AWS Bedrock that lets users create Amazon QuickSight dashboards through natural-language conversation, cutting dashboard build time from ~30 minutes to ~5 minutes. Strong in production concerns (observability, token/cost tracking, model tradeoffs) and in bridging business + technical work, owning pre-sales pitching through delivery with an engineering management background focused on AI product management.”

“Full-stack engineer who built "Workstream AI," an AI-powered engineering visibility product that converts GitHub activity into real-time insights using an event-driven microservices stack (RabbitMQ/Postgres/Express) and GPT-4 with a React frontend. Previously a Founding SWE at a health & wellness startup, building data-driven user management tooling, and also delivered a real-time shuttle tracking/ride request system using Java Spring Boot/Hibernate + React; comfortable owning production deployment details (AWS EC2, DNS, SSL).”

“Robotics software engineer who led system design for an Autonomous Trash Collecting ASV presented at the IEEE ICRA 2025 “Robots in the Wild” workshop, integrating YOLOv8-based perception with ROS autonomy logic to detour for trash while preserving a scientific survey mission. Also built ROS2 UAV capabilities combining ArUco detection, RTAB-Map SLAM, and PX4 integration, with strong simulation (Gazebo/VTD/MSC Adams) and CI/CD QA automation experience.”

“ML/AI engineer with production experience in high-scale banking fraud detection at Truist, building an end-to-end pipeline (Airflow/AWS Glue/Snowflake, PyTorch/sklearn) with automated retraining and Kubernetes-based deployment; delivered measurable gains (22% fewer false positives, 15% higher recall) and reduced manual ops ~40%. Also partnered with clinicians at Kellton to deploy an LLM system for summarizing/classifying clinical notes, improving review time and decision speed.”

“Built a production LLM-powered workflow at Frontier to extract structured signals from messy, high-volume documents and route work to the right teams, replacing a multi-day, error-prone manual process. Emphasizes production reliability with schema/consistency validation, re-prompting and deterministic fallbacks, plus async pipeline optimizations for predictable latency. Experienced with multi-agent orchestration (LangGraph, AutoGen, CrewAI) and AWS workflow tooling (Step Functions, SQS, Lambda), and delivered ~70% safe automation via stakeholder-driven thresholds and human review.”

“ML/NLP engineer with hands-on experience building production systems for unstructured insurance claims and customer data linking. Delivered measurable impact at scale (millions of documents), combining transformer-based NLP, vector search (FAISS/Pinecone), and human-in-the-loop validation, and has strong production workflow/observability practices (Airflow, AWS Batch, Grafana/Prometheus).”

“ML/NLP engineer (Beyond Identity) who built production semantic search and entity-resolution systems over internal security documentation, using LDA + BERT embeddings with FAISS/Pinecone to cut search time by 30%. Also scaled a real-time anomaly detection pipeline to millions of events/day with Spark and AWS Lambda, with strong emphasis on measurable validation (Precision@k, MRR, F1, ARI).”

“Full-stack engineer (Devsinc) who built a seed-stage fintech product (Deaglo) for global investment firms, shipping a real-time FX exposure and hedging dashboard using Next.js App Router + TypeScript with Python/C# microservices. Drove major reliability and performance wins by migrating to an async RabbitMQ architecture (DLQs, idempotency) and optimizing Postgres queries (45% faster), while owning monitoring and post-launch backlog.”

“Software engineer who shipped an end-to-end internal workforce dashboard at Northwestern Mutual, spanning Spring Boot APIs, PostgreSQL schema/query optimization, and a React + TypeScript UI with role-based access and filtering. Has hands-on production experience deploying via GitHub Actions CI/CD to AWS (Docker, EC2, RDS) and resolving performance incidents by tuning database queries and indexes.”

“Built and deployed a production Llama 3-based RAG document Q&A system using FAISS, addressing context-window limits through chunking and keeping retrieval accurate by regularly refreshing embeddings. Has hands-on orchestration experience with LangChain and LlamaIndex for multi-step LLM workflows (including memory management) and collaborates with non-technical teams (e.g., marketing) to deliver AI solutions like recommendation systems.”

“Infrastructure/DevOps engineer (Geico) focused on AWS and Kubernetes at production scale. Has hands-on experience building secure GitHub Actions CI/CD for EKS, provisioning core AWS infrastructure with Terraform/CDK, and leading end-to-end incident response with post-incident automation to prevent recurrence; no direct IBM Power/AIX/PowerHA experience.”

“TSE with hands-on experience troubleshooting customer-reported data issues across APIs and SQL, coordinating with engineering on hotfixes, and translating risk to non-technical stakeholders. Has supported application security workflows using Veracode by generating reports, driving remediation via Jira, and tracking exposure metrics; also assisted customers with SSO setup (client ID/secret).”

“Backend engineer who has shipped both high-throughput real-time systems and production LLM/RAG features. Built a database-free, local-first messaging service (Node/Express/Socket.IO) achieving ~1,500 msgs/sec at <25ms p95, and implemented a Go-based RAG recommendation pipeline with strict JSON/schema validation, catalog grounding, fallbacks, and eval loops that cut hallucinations to ~1–2% while reducing LLM costs ~60%.”

“Senior technologist (25 years experience) who served as chief architect/CTO for a patented software startup that was acquired. Strong at building scalable, robust, technology-agnostic systems and translating technical value into investor-ready narratives (forecasts, roadmaps, documentation). Currently prefers joining an existing founding team as a key technical leader/mentor rather than leading entrepreneurship solo.”

“Built and operated a real-time student event/party discovery platform with map-based search, RSVP, and authentication using React/TypeScript, Node.js, and Firebase Firestore. Demonstrates strong backend correctness under concurrency (transactions, idempotency, retries/backoff) and solid API product thinking (versioning, Swagger docs, structured errors, cursor pagination), including custom geospatial querying via Haversine filtering.”

“Consulting-style LLM practitioner who builds enterprise knowledge assistants using RAG and takes them from prototype to production with guardrails, evaluation, and full-stack observability. Experienced partnering with IT and customer-facing teams to demo solutions, build tailored prototypes, and drive adoption through API-based integration.”

“Full-stack engineer who built an end-to-end low-code/no-code IDE for creating AI/ML workflows for industrial IoT sensors using Next.js/TypeScript and NestJS microservices. Focused on scaling high-volume sensor dashboards—improved UX and performance via WebSockets, debouncing, pagination, and API payload reduction—validated with profiling tools and user feedback in a startup environment.”

“Built and shipped AI-powered workflow automation at Oracle, including an MCP-based agentic workflow with tool-calling and guardrails, plus Grafana monitoring and Confluence documentation. Also led a Django monolith-to-microservices migration at Chamsmobile using blue-green deployment and load balancer traffic splitting to avoid regressions while modernizing production systems.”

Aakanksha Desai

Screened

Junior Full-Stack Software Engineer specializing in React, Kubernetes, and AI-powered apps

Scottsdale, Arizona2y exp

“Backend/DevOps-leaning engineer managing multiple customer service platforms end-to-end (requirements through deployment). Built an in-house Python monitoring/alerting solution for Salesforce-to-Java contact sync jobs (Snowflake dependencies) that increased uptime ~60%, and helped modernize delivery by moving the team from manual releases to automated Jenkins-based deployments while coordinating an Oracle EBS→Fusion transition with business/data/IT stakeholders.”

Shubham Jangle

Screened

Intern Robotics Engineer specializing in autonomous navigation and perception (ROS2)

Riverside, California1y exp

“Recent UC Riverside master’s graduate focused on uncertainty-aware imitation learning for indoor robot navigation, building a full ROS 2 Humble stack (perception, learned policy, uncertainty estimation) with adaptive speed control. Demonstrated strong real-time robotics debugging and systems skills, achieving 92% autonomous navigation success across 100 trials and improving reliability through uncertainty calibration and SLAM/loop-closure optimization.”

“Built a production AI legal search platform that uses a retrieval-first, source-grounded LLM pipeline with confidence-based fallbacks and structured, traceable outputs to reduce hallucinations and improve trust. Also has experience at Discover Excellence building real-time analytics and identity stitching systems, emphasizing conservative data validation, idempotent processing, and fault-tolerant queue-based workflows.”

Cameron Shapoorian

Screened

Mid-level Test Automation & AI Integration Engineer

3y exp

“Forward-deployed/solutions-oriented engineer with experience shipping enterprise LLM voice-agent workflows from prototype to production, including variable extraction and API integrations. Demonstrated strong real-time troubleshooting via logs/RCA (e.g., fixing multilingual language-switching by tuning temperature and improving context), and has led technical workshops while partnering with sales/solutions teams to drive customer adoption.”