Vetted JWT Professionals

Abhishek Soni

Screened

Mid-level Full-Stack Developer specializing in React and scalable web applications

Mumbai, India3y exp

“Backend/data engineer with hands-on production experience across FastAPI microservices and AWS data platforms. Has delivered serverless and Glue/EMR-based ETL pipelines with strong observability (Prometheus/Grafana/Sentry, CloudWatch/SNS), schema-evolution resilience, and measurable SQL performance wins (5 min to <30 sec). Open to onsite meetings in the Bethesda, MD area and flexible on remote arrangements.”

Nithish Nelagal

Screened

Mid-Level Software Engineer specializing in data engineering and cloud platforms

Bentonville, AR3y exp

“Backend-leaning full-stack engineer who has shipped production-critical data/reporting features at Walmart and built an end-to-end workflow automation product (FastAPI + React/TypeScript + PostgreSQL) deployed on AWS. Strong in performance/reliability engineering (parallel ETL, batch DB operations, indexing via EXPLAIN ANALYZE), secure API design (JWT/RBAC), and pragmatic incident-driven scaling (separating workers from API layer).”

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).”

Pranita Agrawal

Screened

Mid-level Software Engineer specializing in Java microservices and AWS

California, USA5y exp

“TypeScript backend/full-stack engineer who owned an internal business workflow platform end-to-end in production, including API/data design, relational DB integration, and enterprise integrations. Has hands-on experience operating workflow processing services with Kafka-style event-driven patterns, idempotency, exponential backoff retries, dead-letter queues, and strong observability, plus API design with OpenAPI/Swagger and token-based auth.”

“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.”

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).”

“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.”

“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.”

“Full-stack engineer with hands-on experience spanning React/TypeScript frontend architecture, .NET/Entity Framework backend services, and database optimization. Has owned end-to-end features like payment processing flows and also helped ship a 0→1 AI developer productivity capability, showing a mix of product sense, startup speed, and practical performance engineering.”

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.”

“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.”