Vetted PostgreSQL Professionals

“Backend/data engineer with hands-on experience building end-to-end data pipelines and Spring Boot services, including systems processing up to 1 million records per day. Demonstrates practical strength in reliability engineering, API versioning, external data ingestion, and early-stage delivery with CI/CD, observability, and pragmatic architecture choices.”

Shreyas Kumar

Screened

Entry-level AI Engineer specializing in LLMs and applied NLP systems

Syracuse, NY1y exp

“Built Lumo, a real-time voice AI companion, owning the product end-to-end across React/TypeScript, FastAPI WebSockets, and PostgreSQL. Stands out for combining deep full-stack systems thinking with voice UX polish, reliability instrumentation, and configurable parent-control guardrails in a multi-tenant setup.”

“Built an AI-driven trading mentor/analytics system combining a React frontend, Spring Boot backend, and FastAPI ML service for stock risk and indicator analysis. Stands out for a pragmatic approach to AI-assisted development: uses AI for acceleration, but manually reviews code line by line, validates outputs against real market behavior, and adds safeguards for unreliable financial data.”

“Full-stack engineer with a strong builder mindset who has shipped both enterprise workflow software and AI-powered assistant platforms. They combine React/TypeScript and Node.js depth with hands-on experience in LLM/RAG systems, vector search, and reusable MCP-based agent infrastructure, and have delivered customer-facing products for enterprise operations teams including 40+ features across two products.”

Bhanu Akepogu

Screened

Mid Software Engineer specializing in backend, full-stack, and AI systems

USA3y exp

“Full-stack engineer with 3+ years of backend and frontend experience who has built production AI products for enterprise document and policy workflows. Stands out for owning end-to-end systems that combine React, FastAPI, RAG, vector search, and AWS deployment, with measurable impact including 65% less manual review time and significantly faster knowledge-query resolution.”

“Backend/data engineer with hands-on production experience across FastAPI microservices and AWS (Lambda, ECS, SQS, RDS, S3), plus Glue/Athena analytics pipelines. Demonstrates strong reliability and operations focus (timeouts/retries, centralized errors, CloudWatch monitoring) and measurable SQL optimization impact (25s to under 2s). Seeking fully remote senior developer role at ~$150k base.”

Jason Gagne

Screened

Executive full-stack engineer specializing in AI, EdTech, and zero-to-one platforms

Remote, USA10y exp

“EdTech-focused startup builder and technical leader who built writing.io from zero to one and scaled it to 200k learners, later creating MindyRoad, an AI-heavy homeschool platform originally for his own family. Former Chief Architect at ParentSquare, bringing a rare mix of hands-on product execution, architecture leadership, and deep enthusiasm for transforming legacy industries.”

“VR/Unity developer with ~3 years building and shipping educational VR games/simulations for EU/Erasmus+ initiatives (disability, elderly, migrant worker audiences). Has delivered 4 VR projects as a solo developer handling everything end-to-end, and also built a Unity WebGL tabletop game featuring Firebase auth/database, localization, customization, and third-party API-based rewards.”

“Entrepreneurial product builder who created chaintrigger.com in response to early Web3 demand for real-time on-chain event reactions, offering an alternative to The Graph Protocol and achieving adoption among games and other Web3 projects. Currently developing new tools, dogfooding internally, and building distribution via personal network and a niche Twitter/X following to gather feedback and iterate quickly.”

“Executive/engineering leader with 18+ years at an established company who helped turn a top-3 telco data opportunity into meaningful revenue and a continuing partnership to launch new data-driven products. Brings a security/privacy-first approach (compliance assessments and documentation) and a structured North Star + technical planning method for building with limited resources; interested in joining an early-stage founding journey with the right vision and team.”

“Engineering leader for a facial-recognition edge platform who drove a full-stack modernization to scale from ~100 edge devices to thousands of locations. Led a major distributed-systems re-architecture (NATS streaming), database migration (MongoDB to PostgreSQL + TimeScaleDB), and UI/API modernization (React), while scaling the team 5→15 and implementing CI/CD + automated QA to improve release velocity and reliability.”

Saketh Kota

Screened

Mid-level Data Scientist / ML Engineer specializing in Generative AI, RAG, and MLOps

Irving, TX4y exp

“Built and productionized a RAG-based LLM research assistant for biomedical and regulatory document search using Mixtral 7B on SageMaker, LangChain, and Milvus, cutting research time by ~40%. Has hands-on multi-cloud MLOps experience across AWS/Azure/GCP with Kubeflow/Airflow/Composer plus Terraform + ArgoCD, and applies rigorous evaluation/monitoring (latency, accuracy, hallucinations). Also partnered with a non-technical PM to deliver an insurance policy Q&A chatbot that reduced customer response time by 30%+.”

Luke Evers

Screened

Director-level engineering leader specializing in full-stack product and e-commerce systems

Remote12y exp

“Candidate is an aspiring founder currently exploring startup ideas and potential collaborators, with firsthand experience as an early employee at VC-backed companies, including joining a current company shortly after seed funding. They have not raised capital themselves but bring early-stage operating exposure and a strong desire to build something they own with a high-trust team.”

“Built a production LLM-powered crypto trading platform in PHP/Laravel that combined RAG, market data, sentiment signals, and operator review workflows to generate buy/sell recommendations. Stands out for a disciplined approach to agentic systems: the application owns orchestration, risk controls, audit trails, and approvals, while the LLM is treated as a bounded advisory component rather than the control plane.”