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Vetted JWT Professionals
Pre-screened and vetted.
Vamshi Raoulakola
Mid-level Full-Stack & Data Engineer specializing in cloud-native systems and FinTech
“Built and shipped production AI search and RAG features for a university portal, including an embeddings-based semantic search layer and a documentation-grounded assistant with citations and anti-hallucination prompting. Also developed scalable, reliable data pipelines integrating Google Ads/GA4/Meta APIs for automated reporting, with strong focus on evaluation loops and retrieval quality improvements (hybrid search, chunking, query-log driven iteration).”
Manas Agarwal
Junior Full-Stack Software Engineer specializing in Python APIs, React, and cloud AI integrations
“Customer-facing software engineer who builds and deploys practical AI/RAG solutions (e.g., an AI assistant for searching billing PDFs) by deeply understanding support workflows and iterating with users. Demonstrates strong production instincts—quickly stabilizing peak-traffic API timeouts with caching/background jobs, then implementing durable fixes with proper monitoring and maintainable code practices.”
Annie Suzan Edwin Arokiaraj Caroline
Junior Full-Stack Software Engineer specializing in distributed systems and data pipelines
“Backend engineer with hands-on experience building distributed data and API platforms (Kafka + Neo4j on Kubernetes), including processing 3M+ NYC taxi trip records and achieving sub-second graph analytics queries. Strong focus on reliability and performance in Python/FastAPI systems—async refactors, caching, timeouts/retries, feature-flagged rollouts, and JWT/RBAC security for production services.”
Benjamin Agyekum
Senior Full-Stack Software Engineer specializing in AI-powered web and mobile applications
“Backend/full-stack TypeScript engineer who has owned end-to-end, production-oriented systems including an AI property management platform (NestJS/Postgres/WebSockets on Google Cloud using Gemini Vision) and an AI logistics platform (Node/Redis queues/Postgres) focused on low-latency, correctness, and observability. Also designed a public GraphQL API and TypeScript SDK for education partners at StudyFetch, citing 40+ partner integrations in the first quarter.”
Himanshu Shivkumar Garg
Senior Full-Stack Java Developer specializing in Healthcare IT and FinTech
“Built and owned an end-to-end HIPAA-compliant Next.js/TypeScript portal at Casedok using a microservices, event-driven architecture with Temporal-orchestrated SAGA workflows. Emphasizes production-grade quality (strict typing, Jest integration tests, CI + mandatory PR reviews) and operational reliability/observability (circuit breakers, idempotency, Prometheus alerts), plus experience designing external-facing APIs with Swagger, JWT, and backward-compatible versioning.”
Sanskar Pandey
Junior Full-Stack Java Developer specializing in FinTech microservices
“Full-stack engineer with production experience building a real-time order tracking system using React + Firebase/Firestore, emphasizing audit-friendly data modeling, state-machine-based status transitions, and strong post-launch ownership (performance, security rules, reliability). Demonstrated measurable frontend performance gains by isolating real-time updates to dynamic components and applying memoization, plus backend reliability patterns (idempotency, retries) and SQL query/index optimization validated with EXPLAIN ANALYZE.”
Abhiram Mullapudi
Mid-level ML Engineer specializing in real-time inference and anomaly detection
“Built DocMind, an end-to-end PDF chat assistant using React/TypeScript, FastAPI, and Postgres/pgvector, showing full-stack ownership plus practical performance tuning and AWS debugging skills. At Social Tech Labs, improved onboarding, shipped lean under ambiguity, and created a reusable low-latency feature serving layer that reduced duplicated infrastructure work across models.”
Anuj More
Mid Full-Stack Engineer specializing in web platforms, geospatial apps, and AI
“Software developer who actively integrates AI coding tools like ClaudeCode, Codex, and ChatGPT into day-to-day development for brainstorming, planning, and reducing boilerplate work. They show thoughtful awareness of agent limitations such as hallucinations and use markdown-based project context files to improve output quality.”
Meghkumar Patel
Intern-level Software Engineer specializing in backend, cloud, and AI systems
“MS Software Engineering candidate at SJSU with hands-on full-stack and applied AI experience, including building DataTrust, a secure enterprise RAG assistant with ABAC-style access control, audit logging, and grounded-answer evaluation. Also built CareerPilot, an AI interview-prep product that turns LLM and speech-to-text outputs into structured, user-friendly feedback for students and job seekers.”
Jignesh Patel
Junior Software Engineer specializing in backend and distributed systems
“Software engineer with a strong builder mindset who has worked across ML, backend, and frontend systems. Notably built an AI-driven predictive autoscaler for Kubernetes from scratch using Prometheus, TensorFlow, Flask, and Spring Boot, and also delivered customer-facing automation features in financial document processing by working directly with auditors to translate domain rules into product logic.”
Shivani Chowdhary
Senior Frontend Architect specializing in FinTech and modern web applications
“Founding frontend developer for StockEdge, a cross-platform stock market analytics SaaS, where they owned UI, branding, frontend architecture, and deployment across web, Android, and iOS. Most compellingly, they helped take the product from 0 to 1 million unique users and 10,000 paid subscribers while building data-heavy, near-real-time financial experiences in React and TypeScript.”
Volodymyr Pisotskyi
Junior Full-Stack Engineer specializing in AI-powered web applications
“Full-stack engineer building production AI/RAG systems for benefits workflows, including a state-level deployment that introduced filestore-based evaluation and improved answer correctness by about 30%. Strong across Next.js, backend infrastructure, and AI evaluation tooling, with hands-on experience in LangChain/LangGraph, Langfuse, accessibility-minded UI work, and zero-to-one product leadership in fast-moving environments.”
Viswanath Jagaluri
Mid-level Full-Stack & AI Engineer specializing in LLM applications
“Full-stack engineer who has shipped and operated generative-AI chat/QA features end-to-end, including a RAG-based pipeline with guardrails and cost/latency monitoring in production. Experienced with React/TypeScript + Node/Postgres architectures, Dockerized deployments to AWS (EC2) via GitHub Actions CI/CD, and building reliable ingestion/ETL systems with idempotency, backfills, and reconciliation.”
Karthik Patralapati
Mid-level AI/ML Software Engineer specializing in GPU-optimized LLM inference and cloud microservices
“Built and deployed a production RAG-based multilingual analytics assistant for healthcare operations, enabling non-technical teams to query claims/EHR and risk metrics with grounded explanations. Demonstrates strong end-to-end LLM system engineering (retrieval tuning, re-ranking, hallucination controls, verification layers) plus workflow orchestration (Airflow/Composer/Step Functions) and stakeholder-driven iteration via prototypes and dashboards.”
Shaktisharan Rajure
Mid-Level Full-Stack Engineer specializing in microservices and cloud APIs
“Software engineer who builds workflow-centric products end-to-end, including a customer-facing module on the Trident AI content platform and an internal content workflow tool adopted as the default process. Strong in TypeScript/React + FastAPI architectures and in scaling event-driven microservices with RabbitMQ, emphasizing reliability (idempotency, DLQs) and observability (correlation IDs) to reduce outages and debugging time.”
Doondi Ashlesh Tammineedi
Junior Full-Stack Software Engineer specializing in cloud-native web apps and AI tooling
“Software engineer with experience across edtech, live gaming, and an AI document intelligence platform, delivering end-to-end customer-facing features and production backends. Built secure, automated live-session scheduling integrating Zoom and TalentLMS (JWT/RBAC, idempotency, transactions) cutting setup time from ~3 minutes to under 1 minute, and optimized real-time gaming dashboards/APIs with query tuning, caching, and CDN improvements (~60% latency reduction under peak load) on AWS.”
Dinal Dholiya
Mid-level Full-Stack Engineer specializing in AI-powered and cloud-native systems
“Product-minded engineer who has owned features end-to-end, including a full onboarding redesign that lifted completion ~25% and a production LLM/RAG report-generation system with strong guardrails (schema-constrained JSON, confidence gating, logging) and an automated eval/regression loop built from real user queries. Also built a scalable research data pipeline ingesting messy PDFs/JSON/CSVs with normalization, idempotent reruns, observability, and cost/latency tradeoffs.”
Saideep Reddy Talusani
Mid-level Backend Engineer specializing in Python APIs and cloud-native services
“Data engineer with experience at Morgan Stanley and Star Health owning production-grade lakehouse pipelines for credit risk and healthcare datasets. Built Azure/Databricks/Delta/Snowflake-based platforms processing millions of records per day with strong data quality, observability (Monte Carlo/Azure Monitor), and reliability practices, plus experience delivering curated data services with performance tuning and backward-compatible versioning.”
Uzair Asif
Senior Full-Stack Software Engineer specializing in cloud-native web, mobile, and AI features
“Frontend lead for a consumer-facing social platform, owning architecture through release. Built scalable React/TypeScript systems (Redux Toolkit, Remix) with a shared Storybook component library and strong quality gates (CI, Jest/Cypress). Experienced modernizing legacy codebases incrementally with feature flags and shipping major dashboard features with staged rollouts and close QA collaboration.”
MANOGNA VADLAMUDI
Junior AI Engineer specializing in LLM evaluation, prompt engineering, and AI orchestration
“LLM workflow builder who has deployed a personalized GPT experience (including Delphi AI-based knowledge ingestion) and built a LangChain/LangGraph job-aggregation pipeline that ingests, normalizes/dedupes, filters, then uses an LLM to rank and summarize matches. Emphasizes production reliability with structured outputs, retries/fallbacks, metric-driven evaluation, logging/prompt versioning, and A/B testing, and collaborates with non-technical stakeholders through demo-driven iteration.”
Varun Mahankali
Junior Full-Stack Software Engineer specializing in React, Node.js, AWS, and Generative AI
“Built and production-deployed a Streamlit-based PDF RAG chatbot using LangChain (FAISS, embeddings, prompt templates) and OpenAI, optimizing Streamlit’s stateless behavior by caching vector DB + chat history to cut latency and API cost. Demonstrates a rigorous evaluation mindset (gold datasets, unit tests, LLM-as-judge, groundedness KPIs) and has experience communicating privacy/accuracy safeguards (RBAC, data masking, citations) to a non-technical client at Kalven Technologies.”
Binaya Sharma
Senior Software Engineer specializing in full-stack systems, big data, and applied AI
“Built and deployed ForensicLLM, a local domain-specific LLaMA-3.1-8B model for digital forensic investigators using RAFT + RAG over 1000+ curated research papers, with citation-aware responses and rigorous evaluation (BERTScore/G-Eval). Deployed via vLLM and Docker and validated through a chatbot survey with 80+ participants; published at DFRWS EU 2025.”
sampath achalla
Mid-Level Software Engineer specializing in backend and full-stack web applications
“Backend engineer focused on scalable, secure, observable systems—built an async workflow backend with REST APIs and state persistence that improved reliability under concurrent load and cut end-to-end processing time ~40%. Strong in production security for multi-tenant systems (OAuth2/JWT, RBAC, DB row-level security) and in low-risk migrations using feature flags and canary releases, including catching and preventing cross-tenant data access issues with CI-based RLS tests.”
William Watanabe
Mid-level Full-Stack Software Engineer specializing in authentication and SolidJS/TypeScript
“Mid-level full-stack engineer (Los Angeles) who built and shipped an end-to-end authentication system for SolidAuth, an open-source SolidStart ecosystem library published to NPM with 1000+ downloads. Experienced designing React/TypeScript + Node + Postgres architectures, operating lightweight production systems on AWS (EC2/S3/RDS/IAM/CloudWatch), and building resilient third-party ingestion/integration flows with idempotency, retries, queues, and backfills; also worked in an early-stage NIL startup (OFFSZN) shipping core onboarding/profile features amid changing requirements.”