Vetted React Professionals

Mike Khorrami

Screened

Director-level Engineering Leader specializing in enterprise SaaS and cloud-native platforms

Woodland Hills, CA25y exp

“Engineering leader/player-coach who modernized a legacy C#/SQL Server system to Snowflake + Python on GCP, enabling ~30x scale and supporting hundreds of millions of transactions per day per customer. Strong in architecture tradeoffs (Snowflake vs Databricks), production reliability (New Relic, logging/alerting), and lightweight process improvements like a rigorous Definition of Done and structured PR reviews.”

“Founder of Business Online Strategic Solutions Digital Marketing, a 5-year bootstrapped digital marketing and web solutions startup serving small-to-mid-sized and enterprise clients. Focused on building scalable, performance-driven web experiences (web dev, UX/UI, CRO, marketing strategy) and is actively scaling capabilities in modern front-end development and AI-assisted workflows.”

“Built production LLM agents at Hivenue and Amazon, spanning consumer booking automation and internal data-query/reporting workflows. Stands out for combining conversational UX with strong reliability engineering—strict tool use, state machines, schema validation, idempotency, and evaluation pipelines—and can point to measurable impact including a 21% reduction in time to book and a 12% conversion lift.”

“Built an LLM-powered customer segmentation agent during a Chewy internship, consolidating Snowflake data into a knowledge graph so non-technical marketing users could query customer cohorts in natural language. Stands out for combining agent/tooling design with rigorous data engineering practices, including schema audits, imputation, validation layers, and idempotent pipelines on messy large-scale datasets.”

“Backend engineer with experience spanning regulated financial systems at Oracle Financial Services and early-stage product building at Apli.ai. Has owned production onboarding infrastructure end-to-end, improved reliability through strong observability and incident response, and also built AI-backed backend workflows using AWS, Bedrock, and RAG.”

“Backend/AI infrastructure engineer focused on production-ready LLM systems and distributed workflows. They described building a RAG-based multi-step agent with strong reliability controls, evaluation loops, and graceful degradation that improved latency by 30%, retrieval accuracy by 15%, and reduced support workload by 40%.”

“Candidate brings a pragmatic, production-focused approach to AI-assisted software development, using AI as a pair programmer and conceptually applying multi-agent workflows across coding, testing, and review. They stand out for putting strong guardrails around AI usage—manual review, testing, SonarQube, peer review, and keeping critical logic manual—to improve speed without compromising security or code quality.”

Ravindrareddy B

Screened

Junior Full-Stack Java Developer specializing in enterprise web applications

Ames, IA2y exp

“Full-stack engineer with hands-on experience building an internal telecom order-tracking/dashboard platform at T-Mobile across React, Spring Boot, and PostgreSQL. Stands out for owning features end-to-end, from scalable frontend architecture and TypeScript patterns to API design, query optimization, CI/CD, and post-launch monitoring in AWS CloudWatch.”

“Software developer who uses AI pragmatically across the full stack to accelerate coding, testing, debugging, and documentation while maintaining strong human oversight. Stands out for treating AI output like any other code source—reviewing for architecture fit, security risks, performance, and standards before integration—and for coordinating multiple AI tools across backend, frontend, and test workflows.”

“Data engineer/backend engineer with healthcare domain experience at Centene, where they owned an end-to-end claims processing pipeline handling over 1 million monthly records. They combine Python/SQL pipeline work with API and event-driven service development, and cite a measurable 35% reduction in incident detection time through automated monitoring and validation.”

Jaya Rathi

Screened

Senior Software Engineer specializing in distributed systems and cloud platforms

Ottawa, Canada15y exp

“Software professional with 13 years of experience across Canada and India, now seeking a first US role in California. Has practical experience applying LLMs and IDE agents like Cursor, ChatGPT, and Gemini to streamline engineering documentation workflows, especially automating Jira/Confluence process work to reduce manual effort and errors.”

bikramjit ganguly

Screened

Staff Full-Stack Engineer specializing in API-driven web platforms and distributed systems

San Jose, CA24y exp

“Highly agent-centric builder who uses Codex daily to generate and manage full application repos, including Next.js CRUD apps, GitHub automation, and AWS lifecycle scripts to avoid long-lived cloud artifacts. They also experiment with multi-agent workflows for parallel development and correctness checking, showing strong practical fluency with emerging AI-native software development patterns.”

Jessy Kattupalli

Screened

Mid-level Full-Stack Java Developer specializing in enterprise web applications

West Haven, CT4y exp

“Backend/full-stack engineer with hands-on experience building enterprise-scale real-time log analysis platforms using Spring Boot, Kafka, React, and observability tooling. Stands out for using AI tools heavily but responsibly—treating them as accelerators while relying on rigorous testing, architectural review, retry/DLQ patterns, and monitoring to ensure production reliability.”

“Engineering leader with 11 years at Nokia/Janus International scaling an engineering organization from 3 to roughly 50 people, plus recent startup experience building an AI-powered virtual property manager platform. Particularly compelling for roles needing a rare mix of hands-on architecture depth, people leadership, and cross-functional execution across backend, web, mobile, QA, and even hardware-integrated products.”

“AI-focused full-stack product builder from Verizon Applied Research who has shipped internal tools spanning API documentation governance, patent exploration agents, and prompt optimization. Particularly strong at turning unreliable or opaque LLM behavior into structured, trustworthy product workflows that enterprise users can actually adopt.”

Rutuja Sanjay Risbood

Screened

Senior Full-Stack Software Developer specializing in enterprise web and mobile applications

San Jose, CA8y exp

“Front-end engineer with unusually deep browser-systems knowledge, having built and owned a real-time merchant analytics platform for financial analysts handling millions of live transactions. Stands out for combining low-level performance engineering, typed React architecture, and expert-user UX polish, with strong measurable outcomes across speed, usability, and maintainability.”

Kunal Mahato

Screened

Mid-level Software Engineer specializing in AI, full-stack systems, and platform engineering

Virginia, USA6y exp

“Full-stack/AI engineer with experience spanning supply-chain product deployments, biomedical agentic search, and research-grade RAG evaluation. Stands out for owning customer-facing migrations at scale (including 216,000 historical shipments), building measurable LLM systems, and pairing AI experimentation with rigorous evals, rollout controls, and auditability.”

Sharath Amula

Screened

Junior Software Engineer specializing in AI and FinTech

Dallas, TX2y exp

“Frontend engineer with experience in both healthcare and financial services, building high-stakes production interfaces such as AI-powered clinician care planning workflows and real-time fraud investigation dashboards. Stands out for combining React/TypeScript performance optimization with strong UX thinking in regulated, data-dense environments.”

“Built and iterated an end-to-end virtual waiting room for a real-time ticketing prototype, making concrete architecture tradeoffs (polling + Redis Pub/Sub) and improving performance post-launch with Redis caching (+30% throughput, -15% p99 latency). Also has hands-on experience building Spark/HDFS ETL pipelines with strong reliability/observability patterns and running disciplined NLP model evaluation loops on review-rating classification.”

“Built Taskline end-to-end as a solo founder: an AI-native operations platform for tradespeople with web and mobile apps, AI receptionists, invoicing, scheduling, and payments. Particularly interesting for teams seeking a zero-to-one full-stack builder who can turn LLM/agent capabilities into practical, low-friction products for non-technical users.”

“Full-stack engineer who owned an enterprise AI agent automation platform at KeyBank, building React/TypeScript interfaces and Python/AWS microservices for document-heavy business workflows. Stands out for translating complex AI automation into usable products for non-technical users, with reported productivity gains of about 35% and reduced manual processing.”

“AI/full-stack product engineer with experience shipping agentic systems in both fintech and enterprise compliance contexts, including an Anthropic-powered compliance Q&A tool at American Express and a home-equity assessment experience for seniors. Stands out for combining strong product instincts, typed full-stack implementation, and rigorous LLM evaluation/monitoring practices to improve trust, adoption, and operational efficiency.”

Nicholas Leytem

Screened

Staff Software Engineer specializing in high-throughput retail data systems

Minneapolis, MN12y exp

“Software engineer at a global public growth company since 2015, with experience owning a legacy Java ETL analytics application and helping design and launch a Kotlin/Java data sourcing platform for customer order data. Brings hands-on experience across React, Spring Boot, AWS/Kubernetes deployment, and multi-database architectures, including an inventive pseudo-graph implementation in DynamoDB to support flexible document matching.”

“Full-stack/backend-leaning engineer with experience spanning fintech platforms, internal AI/RAG assistants, real-time analytics systems, and a zero-to-one academic web platform. Stands out for combining hands-on backend and infrastructure work with product ownership, team guidance, and measurable impact like cutting troubleshooting lookup time from 30 minutes to under 8 minutes and creating reusable UI components adopted across multiple projects.”