Vetted React Professionals

Shruti Krishnagiri

Screened

Executive Engineering Leader & Technical Founder specializing in AI automation platforms

San Francisco Bay Area, California20y exp

“Founder/CTO who built and shipped a consumer subscription-bundling platform end-to-end (architecture, implementation, testing) and scaled it to thousands of customers and major partners. Previously led a major reliability overhaul at Chan Zuckerberg Initiative for a Google-Docs-like ed-tech product—boosted observability, introduced incident management, and migrated to a Docker-based scalable architecture. Heavy user of AI tools (Cursor/Claude) for development, testing, and code review, with a strong bias toward lightweight, fast-moving execution.”

Vivek Anand

Screened

Executive Technology Leader (CIO/CTO/CDO) specializing in AI, cloud, and data strategy

Northbrook, IL20y exp

“Founder with an end-user-ready product who has self-funded/used angel investing but has not yet launched marketing in earnest. Motivated by identifying a market gap with a differentiated product and is now seeking value-add investors who can provide both capital and go-to-market expertise/connections.”

Amit Sharma

Screened

Principal Software Engineer specializing in AI/LLM platforms, payments, and healthcare systems

San Francisco, CA25y exp

“Engineering player-coach who recently shipped an agent-based workflow to extract key info from unstructured web data (browser agents + CDP) and populate daily digests/calendars, owning architecture through testing. Also built a Flask-based LLM evaluation and regression testing system using G-Eval/Confident AI dashboards, and applies a rigorous, research-driven approach to selecting third-party tools with stakeholder buy-in; has healthcare ops/onboarding workflow experience at Vivio Health.”

“Built and owned end-to-end production systems for a healthcare platform, including a predictive task recommendation feature (React + FastAPI + ML on AWS ECS) that cut backlog 20% and saved coordinators ~10 hours/week. Also productionized an AI-native RAG system (vector DB + LLM) delivering 40% faster query resolution, and led phased modernization of a monolithic FastAPI service into async microservices using feature flags and canary releases.”

“Built production-grade Python systems in a medical/imaging context, including an image feature extraction and survival prediction microservice with strong testing, validation, and observability practices. Also developed a Playwright-based autonomous job application agent that handled dynamic UIs and anti-bot challenges with stealth tooling, proxies, and human-in-the-loop escalation.”

Akhil Kunala

Screened

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

Seattle, WA5y exp

“Amazon engineer with 5+ years of experience who built an AI-assisted log investigation and triage workflow that cut debugging time by about 30% during on-call incidents. Combines observability tooling like CloudWatch and Splunk with Python, prompt engineering, and RAG-based diagnostics, and has practical experience orchestrating agentic AI workflows with a strong human-in-the-loop reliability focus.”

Prakash Bhanu

Screened

Director of Software Engineering specializing in cloud, platform, and FinTech systems

Sunnyvale, CA22y exp

“Senior software engineering leader with broad 0-to-1 product experience spanning web apps, microservices, monoliths, messaging platforms, ML/AI products, and large-scale distributed systems. Notable examples include building a payroll/finance product for cast and crew, a distributed messaging platform, and a Walmart application deployed across multiple CDNs and clouds handling hundreds of TPS, with personal ownership across architecture, design, coding, and support.”

“Backend-focused engineer with experience at AWS building a global alarm processing platform (Python, Lambda/SQS/DynamoDB) handling traffic spikes and reliability issues; resolved duplicate alerts and latency under load by fixing hot partitions and enforcing idempotency. Previously at Cognizant, built Java/PostgreSQL backend workflows for healthcare dashboards using pre-aggregated summary tables, strong SQL optimization, and state-driven job orchestration with ELK-based observability and production guardrails.”

Srinivas Vasudevan

Screened

Junior Software Engineer specializing in distributed systems and FinTech

Durham, NC3y exp

“Built an end-to-end payment fraud monitoring dashboard with a React/TypeScript frontend, GraphQL backend, Redis hot path, and a production RAG chatbot, while solving real-time latency and scaling issues. Also shipped an OCR system on AWS EKS for a live manufacturing line at Troxler, improving production accuracy by 15% with custom preprocessing and model tuning.”

“Backend-focused AI engineer with enterprise experience building startup-style internal products at JPMorgan Chase. He helped create an AI-powered financial research platform for analysts, leading retrieval and multi-agent orchestration work that cut research prep from hours to under 20 minutes while scaling across large volumes of SEC filings and earnings transcripts.”

Sanjay Santhanam

Screened

Mid-level AI Software Engineer specializing in LLMs and FinTech data systems

San Jose, CA4y exp

“Backend/AI systems engineer focused on productionizing agentic document-processing workflows for large financial PDFs. They describe owning deployments end-to-end, combining Python, Redis, LLM function calling, RAG/ReAct-style orchestration, and strong reliability practices to deliver 80% faster processing, reduce parsing errors from 12% to ~1%, and sustain 99.9% uptime in high-concurrency environments.”

“Built end-to-end AI features across both fitness and insurance domains, including a full-stack personalized workout recommendation system and a production RAG-based insurance QA assistant at Relevance Labs. Stands out for combining backend/distributed systems skills with practical LLM architecture, evaluation, and risk-aware human-in-the-loop design; notably reduced unnecessary LLM calls by 40% while improving latency and answer reliability.”

“ML engineer with production experience at Goldman Sachs and Medtronic, focused on real-time AI systems in fraud detection and healthcare. Brings a rare mix of backend ML infrastructure, MLOps, and product-minded UX thinking, including dashboard and API design that made complex model outputs usable for analysts and clinical users.”

“Built and productionized an LLM-powered clinical assistant at a healthcare startup, re-architecting a prototype into a robust RAG system on AWS with guardrails, citations, monitoring, and automated tests for clinical reliability. Works closely with clinicians to convert workflow feedback into evaluation criteria and iterative system improvements, and has hands-on experience debugging agentic systems in real time (including during live client demos).”

“Backend engineer who built and evolved an internal multi-agent AI research platform (Electron + FastAPI) integrating OpenAI, focused on fast, reproducible experimentation with strong observability and run metadata for debugging. Has led incremental backend refactors with feature flags and parallel validation, and brings production-grade access control expertise from ServiceNow (table/field ACLs and row-level-style enforcement).”

“Backend engineer with hands-on experience building Flask REST APIs (auth, CRUD, S3 media uploads) and driving measurable Postgres/SQLAlchemy performance gains (p95 reduced to 200–400ms by eliminating N+1s and switching to keyset pagination). Implemented multi-tenant isolation with strict tenant scoping plus Postgres RLS, and built an OpenAI-powered quiz generation pipeline using queued workers, structured JSON outputs, and Celery/Redis optimizations to stabilize high-throughput workloads.”

“Backend engineer focused on scalable, security-first platform architecture—recently built an end-to-end centralized access-control system that launched successfully with ~50k early adopters and was designed to support ~10x traffic growth. Experienced in production authn/authz (token verification, handoff/session migration), and in de-risking migrations via feature flags, phased rollouts, A/B testing, and Splunk-based monitoring.”

“CMU candidate with hands-on experience taking LLM concepts from research prototypes toward production-ready designs (structured outputs, guardrails, failure-scenario evaluation). Also partnered with sales/customer teams at Mazecare to drive adoption with Dontia Alliance (largest dental clinic chain in Singapore) and engaged Singapore government stakeholders, bridging clinical workflow needs with IT security/integration concerns.”

“Frontend-focused engineer with 5 years at Shopify building and maintaining internal tooling. Led modernization from ERB/jQuery to React/TypeScript/GraphQL and improved performance on large datasets with server-side pagination. Also delivered an end-to-end search feature with filters, URL-driven state, pagination, and error correction, using strong review/testing and zero-downtime rollout practices.”

“Cloud infrastructure/product engineer with end-to-end ownership of cloud-native storage/observability products, including taking an internal CMS to Google Cloud Marketplace and scaling to ~40,000 deployments. Strong in Kubernetes-based platforms (Operators, microservices, RabbitMQ) and performance/scalability work (e.g., 200% cluster capacity increase) plus internal tooling that materially improved SRE/QA debugging and release velocity.”

“Has experience improving an ad server workflow by standardizing genre selection with templates, enabling reuse across multiple accounts and measuring success via hours of manual labor saved. Also delivered an internal technical demo on a device-metrics-to-AWS-CloudWatch logging workflow using whiteboarding and PowerPoint to onboard a new team.”

“JavaScript/React-focused engineer with meaningful open-source impact: redesigned cache key normalization for a client-side data fetching/caching library using deterministic hashing, added robust test coverage, and collaborated closely with maintainers through GitHub PRs/issues. Also drives measurable runtime improvements by profiling hot paths, refactoring core abstractions, and validating with benchmarks/load tests; has taken ownership of unowned initiatives like improving relevance/ranking in an internal search platform.”

“Built a production LLM-powered RAG agent for healthcare/insurance operations that retrieves and summarizes patient medical documents with grounded citations, scaling to ~4.5M records. Addressed medical shorthand and terminology by fine-tuning ~120 lightweight DistilBERT models by specialty and validating entities against SNOMED/RxNorm, while using SHAP/LIME and human-in-the-loop review to make decisions explainable to stakeholders.”

“Product/UX designer with hands-on experience designing AI-driven products end-to-end, including an AI shopping assistant (Stylaire) with multimodal conversational search (text/voice/image). Uses rapid prototyping and usability testing to simplify complex flows (e.g., reducing filter overload via progressive disclosure) and collaborates closely with engineers with working knowledge of HTML/CSS and component systems.”