Vetted GraphQL Professionals

“Full-stack developer who has built and shipped both traditional web products and AI-powered applications, including a Spotify playlist-combining app, a recruiter-facing RAG chatbot embedded in a portfolio, and a fine-tuned GPT-2 art review generator. Stands out for combining privacy-conscious engineering, practical LLM guardrails, and scrappy production problem-solving—from queue-based inference systems to newsroom digital transformation with multi-tenant WordPress.”

“Intern-level full-stack engineer who has built across accessibility tech, ad-tech, healthcare software migration, and consumer analytics projects. Stands out for combining hands-on React/frontend work with backend integration, accessibility-aware routing logic, OAuth debugging, and pragmatic product decisions in highly ambiguous environments.”

“AI/full-stack engineer who has built zero-to-one internal products around LLMs, RAG, and NLP pipelines, including a conversational data interface and a production AI agent system. Stands out for combining frontend UX for non-technical users with backend/cloud architecture and measurable impact, including a reported 60% reduction in data retrieval time.”

Abhinava Sai Tirunagari

Screened

Junior Full-Stack Engineer specializing in AI, healthcare, and FinTech systems

Gainesville, FL2y exp

“Frontend-leaning software engineer who built significant parts of an AI platform at Cognura Health, translating complex document-processing and extraction workflows into usable browser interfaces for business and operations teams. Stands out for combining React/TypeScript UI ownership with backend API collaboration, performance tuning, and thoughtful UX for asynchronous AI workflows.”

Nikita Papenkov

Screened

Mid-level Full-Stack Engineer specializing in frontend, Web3, and data visualization

Russia7y exp

“Frontend engineer with hands-on ownership of a complex blockchain launchpad UI, including a solo refactor that unified Solana and Monad flows under one architecture. Their work emphasized feature-flag-driven multi-chain support, real-time data handling, and major bug reduction, with team feedback strong enough that they nearly received a promotion.”

Dolly Shyam

Screened

Mid-level Software Engineer specializing in backend systems and AI-driven platforms

New York, NY4y exp

“Backend-focused developer with primary experience in Python, Node.js, databases, and API development. Served as the sole backend engineer on a customer dashboard project, owning database review, API endpoint creation, and coordination with frontend developers for integration.”

“Software engineer using AI pragmatically to accelerate development while keeping human review central to quality. Has hands-on experience applying AI and lightweight multi-agent workflows in a microservices environment spanning Java Spring Boot APIs, React modules, and Kafka event flows, with strong emphasis on architecture validation and production safeguards.”

Prabhav Karve

Screened

Junior Software Engineer specializing in data engineering and AI applications

Rochester, NY4y exp

“Data engineer/automation builder with experience at Rochester Regional Health and Accenture, focused on replacing fragile manual reporting with production-grade Azure, Python, and Snowflake pipelines. Stands out for combining strong systems thinking, rigorous validation, and practical AI/LLM usage to drive measurable outcomes, including a 34% throughput improvement and support for regulatory reporting that helped avoid €150M in penalties.”

“Front-end engineer focused on sophisticated browser UIs, with strong depth in performance optimization, modular architecture, and workflow-heavy product design. Built a reporting platform from scratch and delivered measurable UX wins, including reducing form latency from 300ms to under 12ms and turning a 2.5-hour image-prep workflow into a 5-minute batch process.”

“Entrepreneur/fintech product builder who raised a $100K pre-seed from ex-Google/Microsoft execs and built a real-time, direct-to-vendor bill pay micropayments platform. Previously helped scale Norton LifeLock to 1M users (2003) and also created Karma LA, a fraud-resistant, verified donation system (including VA veteran verification) aimed at improving trust and conversion in giving.”

“LLM/agentic-systems practitioner who has repeatedly taken LLM-driven pricing/decision services from prototype to production using pilots, guardrails, observability, and staged rollouts. Demonstrates strong real-time incident troubleshooting (dependency timeouts, cached fallbacks) and post-incident hardening (isolation/async/alerts), and also supports go-to-market via developer workshops, technical demos, and sales-aligned POCs.”

“Backend-focused software engineer building distributed, event-driven Java/Spring Boot microservices with Kafka for low-latency, high-frequency processing. Has hands-on experience modernizing a legacy Java system into containerized microservices deployed on Kubernetes with GitHub Actions CI/CD, and has integrated retrieval-based AI components into production workflows; no ROS/robot hardware experience yet.”

“Accenture engineer who built real-time smart mobility products (Verra Mobility) used by both consumers and government agencies, spanning React/TypeScript frontends and Node.js/GraphQL microservices with Kafka. Demonstrated strong delivery and reliability practices (CI/CD, feature flags, automated testing, CloudWatch observability) and achieved a ~20% GraphQL performance improvement supporting 50,000+ daily transactions, plus built an internal ops/support dashboard adopted into daily workflows.”

“Backend/platform engineer with hands-on ownership of Kubernetes GitOps delivery (GitHub Actions + Argo CD) on AWS EKS, including progressive rollouts and reliable rollback across interdependent microservices. Built a Python/FastAPI ML-driven document-processing service (PostgreSQL + S3) to complement existing Spring Boot systems, and implemented Kafka streaming pipelines with Schema Registry plus Prometheus/Grafana observability. Also supported a hybrid cloud-to-on-prem migration for compliance/latency with phased rollout and incremental PostgreSQL migration.”

“Backend/AI engineer with Johnson & Johnson experience building data-heavy payer/claims analytics services (Python/FastAPI, PostgreSQL, AWS) and optimizing them under peak ingestion load via indexing/query tuning and caching. Also shipped an end-to-end RAG feature for clinicians to extract insights from unstructured clinical notes, using constrained prompts and retrieval-confidence guardrails to prevent hallucinations.”

“Backend engineer who has shipped both high-throughput real-time systems and production LLM/RAG features. Built a database-free, local-first messaging service (Node/Express/Socket.IO) achieving ~1,500 msgs/sec at <25ms p95, and implemented a Go-based RAG recommendation pipeline with strict JSON/schema validation, catalog grounding, fallbacks, and eval loops that cut hallucinations to ~1–2% while reducing LLM costs ~60%.”

Aakanksha Desai

Screened

Junior Full-Stack Software Engineer specializing in React, Kubernetes, and AI-powered apps

Scottsdale, Arizona2y exp

“Backend/DevOps-leaning engineer managing multiple customer service platforms end-to-end (requirements through deployment). Built an in-house Python monitoring/alerting solution for Salesforce-to-Java contact sync jobs (Snowflake dependencies) that increased uptime ~60%, and helped modernize delivery by moving the team from manual releases to automated Jenkins-based deployments while coordinating an Oracle EBS→Fusion transition with business/data/IT stakeholders.”

Prasad Krishna

Screened

Mid-level Full-Stack Developer specializing in healthcare analytics and microservices

Remote, USA4y exp

“Built and maintained an air-quality prediction backend in Python/Flask that serves offline-trained ML models to a React dashboard via JSON REST APIs. Demonstrates strong performance focus across the stack—low-latency inference under load, SQLAlchemy/Postgres query optimization, multi-tenant data isolation, and caching/background task strategies for high-throughput systems.”

Srichandan Kota

Screened

Senior Full-Stack AI Engineer specializing in Generative AI and FinTech

Minneapolis, MN6y exp

“Backend engineer who built and owned an AI-powered financial research product end-to-end, using a typed NestJS/GraphQL backend with LangGraph-style agent routing to produce sourced, structured financial analysis. Emphasizes finance-grade correctness (Zod validation, metric registries, unit/empty-result guardrails) while keeping latency low via batching, caching, and fast token streaming, and has led incremental migrations using strangler/feature-flag/shadow traffic patterns.”

Sumanth Gottipati

Screened

Mid-level Full-Stack Software Engineer specializing in cloud-native microservices and FinTech

New York, NY4y exp

“At Delta Airlines, built and shipped a production LLM-powered semantic search/troubleshooting assistant over maintenance logs and operational documentation using OpenAI embeddings and a vector database. Implemented hybrid ranking, query enrichment, and structured filters to improve relevance ~35% while optimizing latency via caching and vector tuning. Also designed a scalable Kafka + AWS (Lambda/SQS) ingestion pipeline with strong reliability/observability and an eval loop using real engineer queries and human review.”

SREYAS GANGJI

Screened

Mid-level Software Engineer specializing in AI/ML backend systems

Chicago, IL4y exp

“AI/data engineer at ZS Associates focused on production-grade agentic systems, FastAPI microservices, and cloud-native ETL/RAG pipelines at significant scale. They’ve built multi-agent validation and diagnostic workflows inspired by their Copilot/KUBEPILOT AI work, supporting 500K+ records per day while improving ML inference performance by ~30% and cutting manual troubleshooting by 60%.”

Rambabu Dhanavath

Screened

Mid-level Software Engineer specializing in backend and cloud-native microservices

United States5y exp

“Backend/cloud engineer with 5 years of experience who has shipped a production internal ops LLM assistant end-to-end using Spring Boot microservices on AWS. Stands out for designing controlled, safety-first agent orchestration with deterministic tool access, Redis/DB-backed recoverable state, and strong observability/evaluation practices to improve reliability in production.”

Ramya Sree Kanijam

Screened

Mid-level Software Engineer specializing in backend systems, cloud, and AI pipelines

Remote, USA3y exp

“Built and owned an end-to-end AI-driven content enrichment pipeline for a news workflow, using n8n, LLM agents, and external APIs to automate ingestion, deduplication, categorization, and approval routing. Stands out for production-minded AI systems work: they improved reliability with schema validation, retries, idempotency, and monitoring, while automating 90% of processing and cutting duplication errors by 95%+.”

Nidhip Patel

Screened

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

United States3y exp

“Backend Java engineer with strong platform/DevOps experience: modernized an insurance claims legacy monolith into DDD-aligned microservices, deployed containerized services on Kubernetes with Jenkins CI/CD and static analysis gates, and implemented GitOps using ArgoCD. Also led major AWS migration planning with dependency mapping and network monitoring to uncover hidden dependencies, and built Kafka-based real-time event streaming with schema-registry-driven evolution.”