Vetted JavaScript Professionals

Sravya Chunduri

Screened

Mid-level AI/ML Engineer specializing in LLM, NLP, and MLOps

Virginia, USA4y exp

“AI/ML Engineer with 3+ years of experience spanning RAG pipelines, MLOps, large-scale data workflow automation, and resilient Playwright-based UI automation. At Black Hawk Network and Wipro, they describe shipping production systems with strong observability and compliance controls, including reducing flaky automation failures from 30% to under 2% and automating 3+ TB/day reconciliation workflows.”

“Full-stack product engineer with hands-on experience shipping React/TypeScript applications on AWS serverless infrastructure with Postgres. Stands out for combining measurable performance optimization (~30% faster APIs), UX improvements that lifted activation by 25%, and pragmatic platform thinking through reusable hooks and safe multi-tenant dashboard customization.”

“Backend engineer with hands-on ownership of production FastAPI systems, from containerized deployment and reverse proxy setup through operations, reliability metrics, and future-state scaling plans. Also brings applied ML experience, having built and integrated a custom CNN-based fruit classification system with confidence-based human review safeguards.”

“Backend engineer with hands-on ownership of a production POS platform, including architecture, CI/CD, Kubernetes deployment, and live incident handling. Also built a RAG-based document Q&A system using OpenAI/Anthropic with hybrid retrieval, evaluation metrics, and fallback logic, showing both traditional backend depth and practical applied AI experience.”

“Backend/data engineer focused on production Python and AWS: built FastAPI REST services and a containerized ECS Fargate + Lambda architecture deployed via Terraform/CI-CD. Strong in data engineering (Glue/S3/Parquet/RDS) and operational reliability (CloudWatch/SNS, retries, schema-evolution handling), with experience modernizing legacy SAS reporting into Python microservices using feature flags and parity validation.”

“Full-stack/AI engineer who has shipped production systems spanning real-time analytics dashboards and an internal LLM-powered knowledge assistant. Experienced with RAG pipelines (embeddings/vector DB, semantic retrieval, query rewriting) plus evaluation loops and guardrails, and builds observable Kafka-based data pipelines monitored with Prometheus/Grafana.”

Harshitha Ayenugula

Screened

Mid Software Engineer specializing in backend and FinTech systems

New Jersey, USA4y exp

“Full-stack engineer with strong ownership of complex web products, including building a real-time collaborative editor end-to-end using React, Spring Boot, WebSockets, Yjs CRDT, PostgreSQL, Redis, and Docker. Stands out for combining product delivery with production reliability and performance work, including reducing QA defects by ~25%, improving internal tool load times to under 2 seconds, and resolving latency issues in live systems.”

“Full-stack/AI product engineer who has shipped both a production-style React finance app and multiple LLM-powered systems end-to-end. Particularly strong in turning early-stage AI concepts into production workflows, including a Bedrock-based multi-turn chatbot with durable session memory and a medical credentialing document parser that cut pipeline failures by 50%+ on large, messy real-world files.”

“Early-stage founder with a privacy-focused concept to simplify at-home self-hosting for services like email, photos, files, and local AI. They are approaching the idea in staged phases to test traction and minimize upfront capital, and have some familiarity with the startup accelerator ecosystem through a Techstars-affiliated company.”

Surya Padmini Konjula

Screened

Mid-level Software Engineer specializing in backend, cloud, and AI for FinTech

San Jose, CA6y exp

“Senior full-stack engineer focused on AI-powered workflow automation and customer support products, with hands-on ownership from React/TypeScript UI through FastAPI microservices, retrieval pipelines, and Kubernetes deployment on GCP. Particularly strong in turning ambiguous zero-to-one AI initiatives into production systems that reduce manual operations, improve turnaround time, and remain reliable through strong orchestration and monitoring practices.”

“Frontend engineer focused on sophisticated real-time operational UIs, with experience building logistics workflow platforms used by managers, analysts, and support teams. Stands out for combining deep browser-performance knowledge with thoughtful interaction design for demanding users in correctness-critical, live-updating systems.”

“Full-stack engineer with a strong builder mentality who has designed greenfield cloud-native ingestion platforms, customer-facing CAD/configuration tools for manufacturing automation, and self-service forecasting products. Particularly compelling is their ability to translate ambiguous workflows into robust systems spanning React, Node.js, shared TypeScript/Zod schemas, cloud queues, and even proprietary hardware runtimes.”

“Frontend engineer with 3 years of professional experience and a Master's degree who has built a React/TypeScript interface for a two-sided marketplace with role-based dashboards and Stripe escrow flows. Stands out for combining security-conscious UI architecture, measurable browser performance optimization, and polished workflow design for demanding users across desktop and mobile.”

“Built a technically demanding OS simulator dashboard in React/TypeScript that visualized memory, CPU registers, and processes with 100ms live updates. Demonstrated strong frontend performance instincts by pre-caching hundreds of DOM elements, using CSS Grid for precise layout, and debugging tricky address-translation and context-switch synchronization issues.”

“Senior product leader who helped transform Submittable from a single-program grant tool into a multi-program impact platform, driving ARR from $20M to $70M+ while improving retention and margins. Particularly strong in enterprise platform strategy and human-centered AI, with a clear philosophy of using AI to augment expert judgment rather than replace it.”

“Built and shipped a production LLM-powered agent for supply chain operations that integrates ERP data and automates multi-step decision-making with tool calling, state management, and structured JSON outputs. Emphasizes production reliability (guardrails, fallbacks, monitoring, idempotency) and reports strong business impact: 40% faster decisions, 30% higher throughput, and 25% efficiency gains.”

“AI/full-stack builder with a track record of shipping practical LLM products in both hackathon and professional settings. Built ScoutR, an agentic football scouting platform that won Best Use of Gemini at HackCU 2026, and at Merkle shipped a GPT-4-based review-tagging tool that cut analyst tagging time by 90%.”

DuyAnh Nguyen

Screened

Mid-level Frontend Engineer specializing in FinTech web applications

Los Angeles, CA4y exp

“Frontend engineer with enterprise experience at Silicon Valley Bank / First Citizens Bank, focused on complex React and TypeScript interfaces. Has built multi-application workflow switching, optimized production rendering performance with profiling tools, and delivered map-based dashboards handling large datasets while keeping UX responsive and maintainable.”

ERIC Beecroft

Screened

Mid-level Full-Stack Engineer specializing in frontend-led FinTech products

8y exp

“Full-stack engineer with leadership experience across fintech and data products, spanning React/TypeScript frontends, Kotlin/Spring and .NET backends, and AWS infrastructure. Stands out for pairing strong product judgment with hands-on execution: they introduced safer progressive rollout patterns, led Google Auth implementation, and contributed to a lending flow that drove an additional $1M in funded loans in 30 days. Recently expanded into AI tooling by building an MCP app for Claude Desktop integrated with internal APIs.”

“Built and shipped a production LLM-driven data harmonization/record-matching pipeline for pharmaceutical datasets, combining normalization, embeddings/vector search, and an LLM validation step. Emphasizes production reliability via guardrails, confidence thresholds, idempotent/retryable stages, and human-in-the-loop fallbacks, with monitoring focused on manual review and error rates to reduce false positives.”

“Engineer with a solutions-engineering profile who has operated at the intersection of enterprise SaaS architecture, customer-facing technical discovery, and implementation in logistics and fintech environments. He has supported high-scale warehouse management systems processing 500,000+ daily transactions, led integration and security discussions, and improved release efficiency by 50% through CI/CD automation.”

Sai Chinthalapudi

Screened

Mid-level Full-Stack .NET Developer specializing in cloud and microservices

United States4y exp

“Software engineer with healthcare platform experience at CVS Health, focused on APIs, SQL performance, and distributed systems. Worked on a 5-6 engineer team building a healthcare simulation platform and drove API/query tuning and caching improvements that cut response times by 50% for real-time, high-volume telemetry workflows.”

“Product-minded full-stack builder who led Ylopo's A-Z Design Studio from initial concept through shipped production system, owning product management, project management, architecture, and development. Also brings distinctive creative-tech experience from Splice, where they built interactive multi-track audio players and contributed to a community-driven music platform with remix and collaboration features.”

Isha math

Screened

Intern-level AI Solutions Engineer specializing in cloud data pipelines and LLM workflows

Remote1y exp

“Front-end/full-stack engineer with hands-on ownership of a React/Next.js interface for a digital archival platform, focused on making complex metadata and retrieval workflows usable for non-technical stakeholders. Stands out for combining UX clarity, accessibility, and browser-level performance optimization, with measurable impact including ~30% workflow efficiency gains and 20% fewer user errors.”