Vetted JavaScript Professionals

“Data/ML engineer in financial services (Northern Trust) who built a production RAG-based LLM system to connect structured transaction/portfolio data with unstructured market and internal documents for risk teams. Strong in end-to-end pipelines (AWS Glue/Airflow/PySpark), entity resolution, and taking models from prototype to reliable daily production with performance tuning (LoRA + TensorRT) and monitoring.”

Ashutosh Khatavkar

Screened ReferencesStrong rec.

Mid-level SDET/Software Engineer specializing in test automation and CI/CD

Syracuse, NY3y exp

“AAA game QA professional from Ubisoft (For Honor) with deep live-service multiplayer experience. Known for owning network/competitive integrity risks and building a custom network simulation tool to reliably reproduce desync issues, accelerating debugging and saving 100+ hours. Strong end-to-end QA process skills spanning test planning, triage, regression, and release verification using JIRA/TestRail.”

“Built a 24/7 Python/LangChain email agent in production with validation, circuit breakers, human-review escalation, and structured observability. Also applied data and automation skills at Community Dreams Foundation, including turning a vague donor-insights request into a usable donor-risk prediction workflow and raising ETL reliability from roughly 85% to 99% by diagnosing SQLite concurrency issues.”

“Frontend/design-systems specialist who has owned large-scale browser UI platforms in Norway's finance and insurance sector at Gjensidige and Fremtind. They stand out for modernizing design systems across fragmented legacy React stacks while improving accessibility, developer experience, and long-term maintainability in regulated environments.”

“Founding AI engineer at an AI SaaS startup who built the full GTM knowledge and retrieval stack for non-technical teams, driving 60% less manual effort and 25% faster deployments. Also brings enterprise B2B SaaS integration experience from Wipro, including external API/documentation work for large-scale partner ecosystems.”

“Full-stack engineer who built and scaled an AI-powered web product (React/Next.js + TypeScript/NestJS) with MongoDB, Redis, and RabbitMQ. Strong in rapid iteration while maintaining production quality—uses versioned APIs, feature flags, CI/CD, and observability (correlation IDs/structured logs) to ship frequently and debug distributed workflows. Also created an internal operations dashboard for real-time visibility and control of background jobs/AI workflows that was adopted quickly by ops and product teams.”

“Frontend/full-stack engineer with enterprise experience at Infosys and hands-on ownership of a full-stack educational platform, MicroExplore. Built React UI architecture plus FastAPI/MongoDB CRUD features end-to-end, and stands out for candid technical judgment around tradeoffs, maintainability, and security gaps he would address in a production-grade next iteration.”

“Frontend engineer with strong depth in React/TypeScript map-heavy applications, including geocoded CSV workflows, Google Maps integrations, and large-scale record management tools. Stands out for diagnosing tricky production issues involving rendering race conditions, stale state, and frontend/backend contract mismatches, then refactoring toward scalable, maintainable architectures.”

Uriel Kluk

Screened ReferencesStrong rec.

Executive CTO specializing in AI, data platforms, and distributed systems

Chicago, IL20y exp

“Former CTO of Mesh Systems for 20 years, now going all-in on building a physical AI product company. He is simultaneously designing four products across eldercare, smart home monitoring, retail theft prevention, and AI-powered building access, with active industry partnerships (Advantech, Compulab) and a potential LATAM pharmacy pilot.”

Ramesh Ramanathan

Screened ReferencesStrong rec.

Executive HR and IT consultant specializing in talent, operations, and AI-enabled business functions

Chantilly, VA20y exp

“High-volume full-desk recruiter who specializes in driving difficult searches to close with tight process discipline. In one standout example, they filled a highly niche Swahili-speaking video journalist role in DC by moving beyond job boards and networking into diaspora communities nationwide, ultimately relocating and closing a candidate from Maine.”

“Full-stack product engineer who independently built and maintained a marketplace app end-to-end, including React/Node/PostgreSQL architecture, real-time chat, S3 uploads, and OpenAI-based listing validation. Also shipped backend-heavy workflow features for a nonprofit upward mobility platform using Supabase edge functions, with a clear focus on security, role checks, and operational reliability.”

Amrit Srivastava

Screened ReferencesStrong rec.

Junior Software Engineer specializing in robotics simulation and machine learning

3y exp

“Undergraduate AI/robotics research assistant who built a city-scale robotics simulation stack for embodied question answering, including JSON-driven environment generation and a ROS 2 pipeline bridging Isaac Sim sensors (CV/LiDAR) to external ML/RL algorithms. Also created and deployed an open-source library workflow tool adopted across multiple local libraries, using GitHub Actions CI/CD for signed releases and automated updates.”

Bhavesh Ittadwar

Screened ReferencesStrong rec.

Senior Full-Stack Engineer specializing in scalable web and cloud systems

USA3y exp

“JavaScript engineer who built a Michelin-specific headless CMS forms platform based on apostrophe-forms, powering forms across 400+ Michelin websites. Designed an extensible, SOLID-aligned modular field architecture with a shared design system, cutting hundreds of lines of per-project code across 10+ implementations while driving cross-device compatibility and performance (BrowserStack, Lighthouse, SSR).”

Michael Forster

Screened ReferencesStrong rec.

Senior Data Engineer specializing in ETL/ELT pipelines and data integration platforms

New York, NY15y exp

“Data engineer/software engineer who led an end-to-end ETL/ELT pipeline at Pearson processing millions of rows of student data nightly, including client-side data prep/validation, SFTP/API ingestion, staging-based SQL validation/transforms, and production loading. Built reliability features like configurable per-client validation thresholds, detailed reporting, concurrency throttling via a custom queue, and multi-source merge/backfill logic to keep nightly loads running even when sources fail.”