Vetted Kubernetes Professionals

Sadiya Bhawania

Screened

Senior Software Engineer specializing in AI and full-stack web platforms

Bay Area, CA6y exp

“Full-stack TypeScript engineer with early-stage startup experience (HomePulse; sole US engineer) who ships and owns production features end-to-end—routing/state design, API contracts, caching/pagination, and post-launch monitoring/optimization. Has delivered performance-sensitive React UIs (virtualized large datasets, React Query caching, Suspense loading patterns) and built durable job-queue workflows with idempotency/retries, plus SQL Server relational modeling for internal ticketing and knowledge-retrieval workflows.”

Mahesh Kota

Screened

Mid-level Full-Stack Java Developer specializing in cloud-native FinTech and Healthcare platforms

New York, NY5y exp

“Backend engineer with production experience building and scaling a Java/Spring Boot payment processing API on AWS (PostgreSQL/Redis) handling a few thousand RPS, including deep performance debugging (connection exhaustion) and observability (CloudWatch, Actuator, Zipkin). Also shipped application-layer AI features (OpenAI email summarizer with feedback loop, ~40% faster agent response times) and designed reliable multi-step workflow orchestration with retries and manual escalation, plus strong SQL tuning and Python engineering practices.”

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).”

“Platform/infra engineer with deep Kubernetes (EKS) and VMware vSphere experience who has led a monolith-to-microservices transition for a credit lending decision platform. Built GitOps-driven Terraform delivery with strong governance, and used LaunchDarkly-based progressive rollouts plus Datadog observability to safely ship multiple times per day (reported ~6x throughput and 1/3 the bugfix tickets vs legacy). Also operates hybrid on-prem/AWS networking (firewall + Transit Gateway, BGP) and has handled high-stakes datacenter migrations (100TB Storage vMotion) under Sev1 conditions.”

“Software developer with hands-on experience refactoring a legacy .NET CMS into a newer API-driven application (ASP.NET MVC, JavaScript/HTML), including dynamic asset migration and resolving team merge conflicts in Bitbucket. Built automated tests with PyTest and used Postman for API validation, and leveraged Splunk for production issue detection; also worked on an end-to-end ticketing/workflow management project with prioritization and verification steps.”

“Built and shipped production LLM agents including an AI patient appointment assistant for Kyron Medical that automated specialist matching and end-to-end booking with email/SMS confirmations and a voice mode. Strong focus on production reliability (double-booking prevention with DB constraints and pre-write checks), deterministic multi-step orchestration with LangGraph, and rigorous monitoring/evaluation using LangSmith trace replay for prompt regression testing.”

Shashank R

Screened

Senior Data Engineer specializing in cloud data platforms and real-time analytics

Las Vegas, NV6y exp

“Data engineer (Credit One) who built and owned real-time financial transaction and credit risk/fraud data systems end-to-end on AWS + Snowflake. Delivered high-scale pipelines (150k events/hour; ~2TB/week), raised data accuracy to 99%, and cut Snowflake costs 42% while adding strong observability, schema-drift handling, and production-grade APIs/documentation.”

“Analytics professional with Intuit experience spanning modern data stack work, behavioral segmentation, and applied AI. They built dbt/Snowflake pipelines powering retention and churn dashboards, automated feedback classification with OpenAI/LangChain, and partnered closely with product and marketing teams to turn analytics into onboarding, targeting, and lifecycle messaging decisions.”

Shashwat Negi

Screened

Mid-level Software Engineer specializing in AI/ML and full-stack systems

San Jose, CA3y exp

“Data Scientist (2–3 years) at ZS Associates who has built and productionized agentic LLM systems, including a LangGraph-based multi-LLM prompt-optimization pipeline for entity extraction deployed as a Spring Boot microservice via Jenkins. Also built an Insightmate.ai chatbot and improved its RAG accuracy by diagnosing vector retrieval issues and implementing HyDE query expansion, while partnering with sales and pharma stakeholders to drive adoption (e.g., Zimmer Biomet platform migration into a multi-year partnership).”

“Analytics professional with hands-on experience building SQL/Python pipelines, customer ID mapping logic, and self-serve BI dashboards across marketing/CRM and regulated aviation reporting environments. Particularly strong in turning messy multi-source data into trusted reporting assets, with repeated claims of major efficiency gains, faster decision-making, and high-confidence stakeholder adoption.”

“Built and owned VividCraft end-to-end, a production AI platform spanning a TypeScript/Next.js frontend and a Python backend with FastAPI, Celery, Redis, PostgreSQL, and AWS. Stands out for reliability-focused systems thinking: designed idempotent job orchestration across 9 AI providers, shipped with extensive automated test coverage, and reports zero production regressions after launch plus zero credit loss through provider outages.”

“ML/AI engineer with hands-on experience building production MLOps systems for predictive maintenance and demand forecasting, including deployment, monitoring, and iterative retraining. Also shipped a RAG-based employee onboarding chatbot integrated with ServiceNow APIs and reports business impact of roughly $300k/month in reduced stockout and overstock costs.”

“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.”

Meet Vyas

Screened

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

Tempe, AZ3y exp

“Software engineer with 3 years at Gap Inc. who led a major modernization from monolith/legacy frontend to a React and Spring Boot microservices architecture, delivering 25% cost savings, 30% faster releases, and 50% performance gains. Also built a 0→1 startup product, MealShare AI, using managed cloud services to rapidly launch a real-time food redistribution platform.”

“Full-stack engineer with hands-on experience building real-time operational products across banking, insurance, and startup e-commerce environments. They’ve owned features end-to-end—from React/TypeScript dashboards and Redux performance tuning to Spring Boot, Kafka, AWS Lambda, and production monitoring—and have also shipped 0→1 capabilities where business impact was immediate, such as reducing overselling through inventory visibility.”

“Built a production-grade LLM document processing and workflow orchestration platform at CBRE for internal operations teams, handling highly variable long-form documents with a reusable architecture involving 50+ coordinated LLM calls per request. Stands out for treating agentic systems like distributed backend infrastructure, with strong emphasis on evaluation, observability, reliability, and vendor-agnostic orchestration across Bedrock, Vertex AI, and OpenAI.”

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.”

Arya Thorat

Screened

Mid-level Software Engineer specializing in cloud-native distributed systems

Texas, USA5y exp

“Full-stack/backend engineer with deep experience building real-time fraud and credit-risk systems. Shipped an event-driven fraud monitoring platform (Kafka→MongoDB/Redis→WebSockets) delivering sub-200ms updates to 3000+ concurrent internal users, and built a Java/Spring Boot credit risk decisioning API that improved turnaround time by 30–40%. Strong AWS production operations (ECS Fargate/RDS/Redis) with proven incident response and performance tuning.”

Amit Verma

Screened

Mid-level Java Full-Stack Engineer specializing in healthcare and enterprise microservices

Birmingham, AL6y exp

“Developer who actively integrates AI tools like Copilot, ChatGPT, and Cursor into day-to-day coding, testing, debugging, and framework learning to improve delivery speed. They also organize multi-agent workflows across code generation, review, testing, and documentation while retaining final ownership of quality and architecture decisions.”

“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.”

“Backend/full-stack engineer who has owned production retail and order/inventory systems end-to-end, using Spring Boot microservices with Kafka event-driven workflows. Strong in production correctness patterns (idempotency, retries/DLQs, schema versioning) plus observability (Prometheus/Grafana) and developer-facing API design (Swagger, OAuth2/JWT, versioning/deprecation). Also built TypeScript/React SPAs and cited ~40% UI performance improvement.”

“Engineering leader focused on developer platforms and identity: led a 5-person team building a multi-tenant IAM framework extending Duende IdentityServer, including governance, API standards, and multi-language SDKs. Drove major API architecture improvements by introducing GraphQL alongside REST, cutting client calls from 4 to 1 and reducing payload size by 60% within 6 months, with strong emphasis on stability (semver, E2E tests, feature flags, blue-green deploys).”

“Infrastructure/Platform engineer with deep production ownership of large IBM Power/AIX estates (70 LPARs, dual VIOS, HMC across two data centers), including live DLPAR tuning and PowerHA clustering for Oracle/WebSphere. Also brings modern DevOps/IaC experience—built GitHub Actions pipelines deploying to Kubernetes with OIDC/Vault secrets and implemented Terraform to provision AWS EKS/VPC/IAM/ALB/RDS with drift detection and controlled rollouts.”