Vetted Docker Professionals

“Candidate is pursuing a CTO role and has helped multiple startups turn early technology concepts into concrete, real-world technical requirements. They cite a systems science and mathematics background, along with experience at JPMorgan Chase, and appear strongest in technical strategy, concept fleshing, and identifying strong people to help teams succeed.”

Amit Dharam

Screened

Junior AI/ML Software Engineer specializing in backend systems and cloud deployment

Tempe, AZ3y exp

“Built multiple end-to-end automation and data systems, including an Accio RAG pipeline combining PDF parsing, FastAPI, Neo4j, and vector search, plus Selenium-based scraping for a virtual try-on product. Stands out for reliability-minded engineering: automated testing, structured logging, validation layers, and a data-driven approach to debugging flaky automation that improved CI pass rates to over 98%.”

“AI/backend engineer who has owned production applied-ML systems end to end, including a Jitsi meeting intelligence platform with custom RoBERTa boundary detection, LLM summarization, and automated retraining from user feedback. Also has healthcare AI experience building a diabetes medication titration system with strict validation, drift monitoring, and safety guardrails—showing both product speed and high-stakes engineering rigor.”

“Backend/product-minded engineer from Ramp with strong travel-tech experience, having built an end-to-end booking platform integrating multiple external providers, policy enforcement, and reporting infrastructure. They also shipped an LLM-powered personalization workflow using embeddings and Google Gemini that cut trip planning time by 22%, and demonstrated strong production reliability instincts through circuit breakers, health checks, and schema-driven normalization.”

“AI/LLM engineer with strong healthcare domain depth who has shipped production-grade agents for care coordination and clinical workflow automation. Stands out for combining Knowledge Graph RAG, LangGraph orchestration, and rigorous eval/guardrail systems to improve reliability in high-stakes environments, with measurable gains in review time, hallucination reduction, latency, and clinician adoption.”

“Full-stack product engineer who has built end-to-end apps and internal tools spanning React/TypeScript, Node/Express, and Postgres. Stands out for pragmatic shipping under ambiguity, creating reusable platform primitives like a centralized notification API, and designing safe multi-tenant configurable dashboards with schema validation.”

“Product-minded full-stack engineer who has built AI-heavy systems spanning Next.js/TypeScript frontends, Python/FastAPI backends, queues, databases, and workflow infrastructure. Stands out for combining strong technical depth with UX instincts—improving trust in AI assistants, shipping ambiguous client features quickly, and creating reusable primitives for AI generation and analysis products.”

“ML/AI engineer with hands-on ownership of a production LLM/RAG system at Goldman Sachs, focused on workflow automation and large-scale document search for operational teams. They combine strong MLOps and backend engineering skills with practical GenAI evaluation and safety practices, and cite measurable impact including 22% better task guidance accuracy and sub-second search across millions of records.”

“Data engineer with a Master's in Data Science who has owned 30+ customer-facing K-12 SIS migrations end-to-end, building ETL, validation, and SOP-driven deployment processes in a PII-sensitive environment. Also brings recent hands-on agentic AI experience from a biotech capstone, where they led a production-oriented NLP-to-SQL + RAG support system that handled about 30% of support queries in testing.”

“AI/ML engineer who has built a production text-to-image generation system in PyTorch with an AWS-backed inference setup, focusing on GPU-efficient training and embedding-space architectural choices inspired by recent research (e.g., Meta VL-JEPA). Uses both metric-based evaluation (FID) and human testing to validate real-world visual quality, and can translate technical concepts for non-technical stakeholders.”

“Product-minded full-stack engineer with experience shipping engagement features and core communication systems at DribbleUp and Expys. Stands out for combining rapid MVP execution with rigorous iteration: delivered a leaderboard feature that lifted engagement by 8% initially and 20% overall, built a chat MVP in 3 days, and has hands-on experience deploying LangChain-based concierge agents with evals and human review.”

Keerthi Pericherla

Screened

Mid-level Full-Stack Developer specializing in cloud-native FinTech applications

Remote, USA5y exp

“Frontend engineer with HCL Tech experience building loan operations dashboards and React/TypeScript data-heavy interfaces. Stands out for combining maintainable component architecture with hands-on performance tuning, including a reported 30% load-time improvement in a production visualization-heavy application.”

PavanKumar Varkala

Screened

Mid-level Full-Stack Engineer specializing in AI-driven web applications

Jersey City, NJ4y exp

“Built and shipped an AI-driven operational workflow platform at Adobe that handled 12k+ monthly requests using React, Node.js, TypeScript, OpenAI APIs, PostgreSQL, Redis, and RAG. Stands out for combining full-stack product ownership with production-grade LLM architecture, evals, and human-in-the-loop controls, delivering measurable gains including 38% higher accuracy and 40% less manual triage.”

Raymond Hunce

Screened

Senior Software Engineer specializing in full-stack platforms and cloud systems

New York, NY5y exp

“Frontend-leaning full-stack engineer with 5+ years of professional experience across startups and Capital One, combining UI design instincts with hands-on React/TypeScript implementation. Has owned polished browser interfaces end-to-end, built custom analytics instrumentation with DynamoDB, and improved complex internal tooling by redesigning data-heavy workflows based on direct user feedback.”

“Built full-stack features for an AI healthcare copilot at Prompt Opinion, combining React/Next.js, Node/Express, PostgreSQL, and LLM/MCP integrations over FHIR-compliant patient data. Stands out for healthcare data interoperability knowledge, production ownership, and measurable impact, including scaling chatbot throughput and improving model response accuracy by 30% through better MCP tool architecture.”

“Frontend-focused product engineer with hands-on experience designing and shipping real-time dashboards and alerting systems in regulated domains like banking and healthcare. Has led both UX/design and implementation work, combining React/TypeScript and Angular frontend expertise with Kafka-driven event architectures, performance optimization, and production monitoring.”

“Frontend-focused product engineer with experience at IBM and Intel building internal enterprise platforms, especially incentive and employee operations workflows. They repeatedly describe owning both UX/design decisions and the React frontend implementation, with strong emphasis on reusable components, API integration, and shipping ambiguous workflow products into production.”

Uma mahesh

Screened

Mid-level AI Software Engineer specializing in Generative AI and healthcare automation

NC, USA5y exp

“Backend/AI engineer with 5+ years spanning ServiceNow, Cognizant, and GE Healthcare, where they built agentic AI and RAG systems for safety-critical medical device workflows. Particularly compelling for teams needing production LLM systems in regulated environments: they combine cloud deployment and evaluation rigor with HIPAA-aware privacy controls, explainability, and measurable business impact.”

Ziyu Wang

Screened

Mid-level Full-Stack Engineer specializing in AI platforms and agents

New York, NY4y exp

“Front-end engineer focused on high-performance real-time browser applications, with hands-on ownership of an AI-integrated education platform and interactive admin tooling. Stands out for deep browser fundamentals knowledge and measurable UI performance gains, including a 40% reduction in client-side response latency.”

“Frontend engineer with strong React/TypeScript depth who built a schema-driven onboarding platform in Next.js and Apollo GraphQL to support client-specific workflows without duplicating forms. Demonstrates solid performance instincts, having diagnosed and improved lag in a production cart/order dashboard using React DevTools Profiler, memoization, debounced filters, and state isolation.”

“Full-stack engineer who described a sophisticated forum platform spanning Next.js, NestJS, MongoDB, MySQL, PostgreSQL, RabbitMQ, and AWS. Stands out for strong systems thinking: they designed for type safety, eventual consistency, idempotent async moderation, analytics scalability, and production reliability, while also driving an architectural refactor that reduced new post-type delivery from multi-day work to about half a day.”

“Robotics software engineer with hands-on experience across reinforcement learning and ROS/ROS2, including a project teaching Boston Dynamics Spot to open a door by combining vision-based pose estimation with SAC-trained IK and a walking policy in MuJoCo. Previously built ROS Noetic control for surgical robots using RCM with MoveIt IK and achieved sub-0.02s latency via threading; also participated in a NASA ROS2 space simulation building rover teleop and sensor-driven mapping.”

“Founding Principal Engineer/Head of Engineering at Amberflo (Seed $5M Homebrew; Series A Norwest) who built and shipped an AI Gateway + real-time LLM cost metering/pricing MVP end-to-end (control plane/data plane, AWS infra, CI/CD). Known for extremely fast MVP cycles (often 1–2 weeks), scaling teams (50–60 hires), and driving major pivots (usage-based billing to FinOps) by repurposing an existing metering/pricing platform; based in Chicago and has led a Silicon Valley startup remotely with frequent Bay Area travel.”

“Platform-focused engineer/technical program leader working in silicon/wafer validation environments, with hands-on experience securing access to sensitive test results and engineering tooling. Has implemented RBAC/least-privilege controls with Azure Entra ID, Key Vault, PAM and integrated Checkmarx into dev workflows, while also deploying ML services on AKS using Bicep/Helm/Docker and Azure DevOps CI/CD with strong monitoring and incident response practices.”