Vetted WebSockets Professionals

“Backend engineer who optimized an AI-driven portfolio analytics/insights platform at Fidelity, addressing latency and traffic growth by moving services toward microservices, improving service communication, and tuning API/DB performance. Experienced scaling Python/FastAPI services with Docker + Kubernetes autoscaling, and strengthening security/privacy for sensitive client portfolio data used in LLM-based reporting.”

“Product-minded full-stack engineer at a B2B startup who ships high-stakes customer-facing features fast: delivered a Spanish AI support agent in 2 weeks by benchmarking LLMs and using native Spanish system prompts, reaching 90% resolution. Built the company’s first monetization system (hybrid subscription + usage) with Stripe/Firebase, emphasizing secure JWT-based flows and idempotent webhooks, and led a microservices decoupling effort that cut developer onboarding time by 50%.”

“Built and deployed a production LLM-powered RAG assistant for healthcare teams (care managers/support) to answer questions from clinical and policy documentation, emphasizing trustworthiness via improved retrieval, reranking, and strict grounding prompts to reduce hallucinations. Also has hands-on orchestration experience with Apache Airflow for end-to-end ETL/ML workflows and applies rigorous testing/metrics (hallucination rate, tool-call accuracy, latency, cost) to ensure reliable AI agent behavior.”

“Backend/data engineer focused on production-grade Python microservices and AWS platforms, including a hybrid Lambda + ECS Fargate architecture managed with Terraform and CI/CD. Has hands-on reliability experience (JWT/OAuth, timeouts, retries, centralized error classification) and built AWS Glue/PySpark ETL pipelines consolidating PostgreSQL/RDS, MongoDB, and S3 sources into curated partitioned Parquet datasets. Demonstrated measurable SQL tuning impact (8 minutes to 25 seconds) and disciplined legacy-to-modern migrations with parity validation and UAT sign-off.”

“Backend/DevOps-leaning engineer with trading/financial systems experience (AIG), focused on reliability: built Python automated test suites to ~95% coverage and integrated them into CI/CD. Has hands-on Kubernetes microservices deployment with GitOps (ArgoCD), plus experience supporting cloud-to-on-prem migrations and building real-time streaming pipelines resilient to spikes and data loss.”

“Backend Python engineer who owned an AI-driven healthcare staffing matching service, rebuilding the model inference/data pipeline to eliminate blocking bottlenecks and cutting API latency by ~33%. Experienced running Python services on Kubernetes with GitOps/ArgoCD, and has executed a cloud-to-on-prem rollout under tight resource and tooling constraints while also building event-driven streaming updates via a message broker.”

“Backend/full-stack engineer with finance domain experience (State Street) who built and shipped a Kafka-based real-time trade validation system handling 50k+ trades/sec and cut latency by 42%. Also delivered real-time React dashboards (Redux Toolkit/React Query/WebSockets) and operates AWS EKS microservices with GitOps/ArgoCD; has built a FastAPI + LangChain/GPT-4 intelligent document processing service with JWT/RBAC.”

“Backend/AI engineer who has built production Spring Boot APIs on AWS (JWT auth, Redis/MySQL) and solved a real-world silent data integrity issue by implementing idempotency keys plus DB constraints/transactions. Also shipped an LLM-based document Q&A feature using a RAG pipeline with evaluation + human review, and designed multi-step agent workflows with verification, retries, and escalation guardrails.”

“Infrastructure/operations engineer with hands-on production IBM Power/AIX (AIX 7.x, VIOS, HMC) and PowerHA/HACMP clustering experience, including DLPAR changes, failover testing, and incident recovery. Also delivers modern cloud DevOps work—GitHub Actions CI/CD for Docker-to-Kubernetes on AWS and Terraform-based provisioning of core AWS infrastructure (VPC/EKS/RDS/IAM) with controlled rollouts and drift checks.”

“Founding/solo engineer who rebuilt an early-stage product from the ground up: Ask NETA, an AI assistant for electricians to answer complex electrical code questions. Delivered a full-stack TypeScript system (React web + React Native iOS/Android, Express API, Postgres on AWS) with CI/CD, observability, and a Vertex AI RAG pipeline, reaching 3,000 MAUs in the first month; also built a real-time distributed scoring system handling unreliable hardware data with sequencing and retries.”

“Full-stack engineer with hands-on production experience building real-time customer-facing features (order tracking + push notifications) across React/React Native and Node/Spring Boot with Postgres/MySQL. Demonstrates strong reliability patterns (transactional outbox, background workers, idempotent webhook ingestion) and has deployed/operated systems on AWS (ECS/Fargate/ALB, CloudWatch, CodePipeline) with structured observability and environment separation.”

“Founding engineer at Novum AI building a real-time call analytics/suggestion backend (transcription + sentiment/tone + context retrieval) using a serverless architecture. Drove major latency improvements (about 4s down to sub-1.5s) and has practical experience hardening production APIs (FastAPI/Pydantic, auth with Cognito/Redis) and payment systems (Stripe) by surfacing overlooked subscription and multi-tenant billing edge cases.”

Ganesh Pittala

Screened

Senior Software Engineer specializing in distributed systems and cloud-native platforms

New York, USA5y exp

“Backend-leaning full-stack engineer with experience at Walmart, Qualtrics, and American Express, shipping secure partner-facing API platforms and internal monitoring dashboards. Strong in AWS production operations (ECS/Fargate, RDS/Postgres, CloudWatch) plus rigorous testing/security practices, with measurable delivery and performance improvements (35% faster releases; ~30–40% latency reductions).”

Prasanth Sai

Screened

Mid-level Data Engineer specializing in cloud lakehouse/warehouse pipelines

4y exp

“Data engineer with HCA Healthcare experience building and operating end-to-end AWS-based pipelines for clinical and operational reporting (50–100 GB/day), serving curated data into Redshift/Snowflake for Power BI/Tableau. Emphasizes production reliability (Airflow SLAs/retries/alerting, logging/observability) and strong data quality controls (reconciliations, schema/null/duplicate checks), and has shipped versioned REST APIs to expose warehouse data to downstream systems.”

“Full-stack JavaScript engineer (React/Node/Vue) who has operated like a maintainer by owning an internal component library with Storybook-style examples, documentation, and non-breaking versioning. Demonstrated strong performance engineering on a source code review service—profiling bottlenecks, fixing N+1 queries, adding caching, and trimming payloads to cut latency (e.g., ~100ms to <50ms) while rolling out incremental, test-backed improvements.”

“Built from scratch a social media analytics MVP featuring an LLM-powered semantic search agent that became a core part of the product experience within a 6-week deadline. Stands out for focusing on production readiness early—retrieval-first design, explicit tool constraints, structured outputs, idempotent services, and practical eval/monitoring loops rather than demo-only AI.”

“Built a prediction market analytics website from scratch to analyze volume and correlations in decentralized markets, drawing on a sports and finance background. Shows strong early-stage product instincts, backend ownership, and a pragmatic approach to scalability, security, and AI-assisted data workflows.”

Surya Ravula

Screened

Junior Software Engineer specializing in backend systems and AI automation

Hyderabad, India2y exp

“Backend/platform engineer with Boston Scientific experience building secure healthcare integrations, resilient AWS data pipelines, and a production internal LLM support chatbot. Stands out for combining legacy-system modernization, strong reliability practices, and measurable operational impact in regulated healthcare environments.”

“Built both a React/Supabase kanban product and CodeVoyage, a multi-agent platform for navigating large TypeScript/Node.js codebases. Stands out for being unusually rigorous about AI-assisted development: they quantify AI usage, manually verify generated code, and have firsthand experience debugging failures in persistence layers, retrieval quality, and long-context agent orchestration.”

“Graduate student who has built both full-stack web products and an offline Android AI assistant for visually impaired users. Particularly interesting for roles spanning product engineering and applied AI, with hands-on experience in on-device ML, privacy-sensitive deployment, and making complex AI interactions usable for non-technical users.”

Indra Shakya

Screened

Senior Full-Stack Engineer specializing in FinTech

Charlotte, NC8y exp

“Frontend-leaning full-stack engineer with deep experience building real-time financial trading platforms at Bank of America. They led modernization of a global markets product by consolidating three legacy apps into a single React/Next.js platform, built WebSocket-driven market data experiences, and helped drive shared component libraries and engineering standards used across multiple teams.”

Saipraneeth Ketireddi

Screened

Mid-level AI/ML Engineer specializing in LLM automation and healthcare analytics

Dallas, TX4y exp

“Full-stack AI engineer who has repeatedly taken ambiguous automation and agentic products from prototype to production, including a BRD automation platform that cut manual processing by 70% and a healthcare RAG assistant with long-term memory. Stands out for combining backend/AI orchestration depth with strong product instincts around trust, observability, security, and non-technical user experience.”

“Frontend engineer with experience building backend-driven UI systems (JSON-schema-based rendering) to enable rapid business-driven screen changes, including collaboration across design/backend/product/QA at Ozon Seller Center. Also created an internal npm package that generates TypeScript API clients from OpenAPI docs—initially for one project, later rolled out company-wide with CI testing and version pinning support.”