Vetted SQL Professionals

“Backend-leaning full-stack engineer who has shipped both a SaaS analytics/A-B testing platform and an AI-driven fraud monitoring product in production. Stands out for combining React/TypeScript frontend work with Python/Java backend systems, event-driven architecture, and practical LLM integration grounded by validation and human analyst feedback, with measurable impact on engagement, performance, fraud accuracy, and false positives.”

Yujun Liu

Screened

Junior AI software engineer specializing in agentic workflows and cloud platforms

Cambridge, MA3y exp

“AI/full-stack builder who has owned end-to-end LLM features in both creative tooling and education workflows. Built a multi-agent film-production workspace for Backlot and an automated ingestion pipeline at iOffer.AI that cut counselor manual entry by 70%, with hands-on depth in orchestration, validation, monitoring, and human-in-the-loop system design.”

Jalaan Fields

Screened

Mid-level finance and strategy analyst specializing in valuation and performance analytics

Remote7y exp

“Co-founder of ATW Labs who built a consulting and analytics pipeline from scratch, selling into middle-market companies and converting outreach into repeat client engagements. Brings a blend of founder empathy, executive-facing business development, and early conviction around practical generative AI use cases, with experience translating ambiguous client needs into high-ROI recommendations.”

Omkar Tulsidas Parab

Screened

Mid-level Software Engineer specializing in full-stack web and AI applications

United States5y exp

“Software engineer who owned an Order Management System end-to-end at Reliance Jio, improving large-table performance via UI virtualization shipped behind feature flags and refined through direct ops-user observation. Also built an OCR automation tool at Piramal Realty using Python/Tesseract with validation and manual correction fallbacks, driving adoption by operations teams. Experienced integrating with Kafka-based microservices and improving observability using structured logging and correlation IDs.”

“Yogesh is an AI/full-stack engineer from LangChain who says he was the sole developer and core maintainer of OpenSWE/OpenSpeed, an asynchronous coding agent in LangSmith Cloud that turns requests from Slack, Linear, and GitHub into reviewable PRs. He emphasizes production-grade agent infrastructure: event-driven workflow design, typed run states, observability, retries, and latency improvements via pre-warmed sandboxes.”

“Full Stack Software Engineer with enterprise experience across healthcare, insurance, and internal SaaS systems, combining React/TypeScript/Node.js depth with hands-on LLM feature delivery. Stands out for building secure RBAC architecture and shipping production AI workflow assistance with strong guardrails, monitoring, and human-in-the-loop decisioning in regulated environments.”

“AI/full-stack engineer with hands-on experience shipping both computer vision and LLM products in production across marketplace and healthcare settings. Built an automated device grading system at Northladder and improved a Deloitte healthcare chatbot using RAG, with a strong emphasis on grounding, validation, uncertainty handling, and human review for high-impact decisions.”

Jaisurya Kolluru

Screened

Mid-level Software Engineer specializing in cloud-native backend and AI systems

Virginia, USA5y exp

“Full-stack engineer with hands-on ownership across React/TypeScript frontends, Node.js backends, and PostgreSQL on AWS. Stands out for production-focused database optimization, including execution-plan analysis, indexing, safe migrations, and architectural improvements that reduced database bottlenecks through a centralized REST API layer.”

“Backend-leaning engineer at Coforge with strong experience in subscription lifecycle and billing platforms, combining PostgreSQL, MongoDB, Azure, Kubernetes, and messaging systems. Stands out for owning production systems end to end and driving an event-driven architecture shift that reduced failures by 30%+ and improved response times by 40%.”

“Full-stack engineer with hands-on experience building enterprise workflow management platforms across React/TypeScript, Node.js/Express, Angular, and .NET Core microservices. They stand out for owning features through production, solving real-world data consistency and legacy-data issues, and driving architectural and SQL performance improvements that made dashboards faster and more reliable.”

“Former Defense Intelligence Agency analyst turned startup operator, venture investor, and chief of staff with a strong track record in lean, high-ambiguity environments. Brings a rare blend of intelligence-style synthesis, startup execution, and institutional capital formation experience, including supporting a $10M Series A raise and helping drive fundraising for a $400M fund across Gulf, MENA, and US markets.”

“Frontend engineer with startup experience building production React applications, including authenticated dashboards, reusable component systems, and Mapbox-based data visualizations. Stands out for translating Figma designs into pixel-accurate interfaces while making pragmatic UX decisions around pagination, mobile usability, and data-heavy screens.”

“Backend engineer with experience at KPMG evolving an audit/reporting platform from monolithic components to microservices (Spring Boot/Node.js), improving API performance and enabling independent deployments. Demonstrates strong production focus across secure API design (FastAPI, JWT/OAuth2, RBAC/RLS), incremental migrations with feature flags, and robustness improvements like optimistic locking to prevent race conditions.”

“LLM/agentic systems practitioner who repeatedly takes customer-facing LLM prototypes into production by operationalizing prompts, hardening RAG pipelines, and adding monitoring/guardrails. Has hands-on experience debugging intermittent production failures under high traffic (vector store timeouts/empty retrieval) and implementing fail-safe behavior plus alerting. Also partners closely with sales in pilots/POCs, customizing demos with customer data and running side-by-side comparisons to drive adoption.”

“Healthcare-focused LLM engineer who deployed a production triage and clinical knowledge retrieval assistant using RAG and LangGraph-orchestrated multi-agent workflows. Emphasizes clinical safety and compliance with robust hallucination controls, HIPAA/PHI protections (tokenization, encryption, audit logging, zero-retention), and human-in-the-loop escalation; reports a 75% latency reduction in a healthcare agent system.”

“AI/LLM engineer who built a production intelligent support system using RAG over a vectorized documentation library, addressing real-world issues like lost-in-the-middle context failures and doc freshness via automated GitHub-driven re-embedding pipelines. Emphasizes rigorous agent evaluation (component/E2E/ops) and prefers lightweight, decoupled workflow automation using message brokers (Redis/RabbitMQ) over heavyweight orchestration frameworks.”

“ML practitioner with a QA background who has built end-to-end ML pipelines for a health risk prediction use case (lifestyle + demographics), emphasizing robustness through strict data validation, leakage prevention, and cross-validation. Collaborated with a dietician to sanity-check predictions and refine feature interpretation for real-world practicality; has not yet deployed LLM/AI systems to production and has no hands-on orchestration framework experience but is willing to learn.”

“Built a production multi-agent orchestration platform to automate healthcare claims and HR workflows, combining LangChain/CrewAI/AutoGPT with RAG (FAISS/Pinecone) and fine-tuned open-source LLMs (LLaMA/Mistral/Falcon) in private Azure ML environments to meet HIPAA requirements. Emphasizes rigorous agent evaluation/observability (trajectory eval, adversarial testing, LLM-as-judge, drift monitoring) and reports measurable outcomes including 35% faster claims processing and 40% fewer chatbot errors.”

“Telecom (Verizon) AI/ML practitioner who built a production multimodal system that ingests messy customer issue reports (calls, chats, emails, screenshots, videos) and turns them into confidence-scored incident summaries with reproducible steps and evidence links. Also built KPI/alarm-to-ticket correlation to rank likely root-cause domains (RAN/Core/Transport), cutting triage from hours to minutes and improving MTTR.”

“Software engineer/product-focused builder who delivered real-time supply chain inventory dashboards to replace a legacy system, integrating directly with ERP/WMS/TMS to eliminate manual reporting. Uses TypeScript/React with Redux Toolkit on the frontend and microservices + REST APIs on the backend, with performance improvements via Redis caching and a strong focus on user-feedback-driven prioritization and observability in distributed systems.”

“Frontend/platform-leaning engineer who owned a shared React component library (design-system style) adopted across multiple SPAs, with strong discipline around SemVer, deprecation strategy, and developer documentation. Also has backend/distributed-systems experience diagnosing and fixing a Kafka microservice race condition and has led prioritization/migration planning in an unstructured monolith-to-microservices environment (Centene).”

“Full Stack Developer (recently at Cisco Systems) building end-to-end web applications with Angular frontends and Spring Boot microservices backed by MySQL/JPA, including JWT + role-based access. Has hands-on experience with high-volume, real-time data processing/visualization and has solved complex UI state consistency issues using RxJS BehaviorSubjects; also applies layered state patterns in React with Redux Toolkit and uses AI dev tools (Cursor/Claude) strategically.”

“Full Stack Engineer with hands-on experience owning customer-facing products end-to-end, emphasizing fast iteration via feature flags and risk-based testing for critical user flows. Built TypeScript/React systems with shared types and clean backend layering, and has microservices experience using RabbitMQ to decouple services and manage scale issues like queue backlogs. Also created an internal dashboard for dev/QA to centralize build/test/deploy visibility and iterated on it through lightweight user research and usage metrics.”