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Vetted GitHub Actions Professionals
Pre-screened and vetted.
Navyanth Bollareddy
Junior Full-Stack Software Engineer specializing in React/Node, cloud, and LLM-powered automation
“Master’s program project lead who built and deployed a real-time sound recognition system (Flask + React Native + ML) that was adopted by 200+ university students. Demonstrates strong production engineering and cross-layer debugging—solving latency, unreliable uploads, and observability gaps using microservice separation, chunked/idempotent transfers, and packet-capture-driven network diagnosis—plus AWS/on-prem and IoT edge-to-cloud integration experience.”
Sudheer Kumar Divvela
Mid-level GenAI Engineer specializing in RAG, LLM agents, and enterprise automation
“Accenture engineer who built and shipped a production RAG-based automation/chatbot for SAP incident triage and troubleshooting, embedding thousands of runbooks/logs/tickets into a semantic search pipeline and integrating it into Teams/Slack. Reported major productivity gains (30–60% time reduction), >90% validated answer accuracy, and sub-2-second responses, with strong orchestration (Airflow/Prefect/LangGraph) and reliability practices (guardrails, testing, monitoring).”
KrishnaVardhan Mandanapu
Mid-Level Software Development Engineer specializing in GenAI automation and cloud systems
“Backend Python engineer who architected an event-driven order integration engine connecting EDI vendors to ERP/WMS/3PL systems, including a canonical order model and adapter framework to eliminate per-customer hardcoding. Has hands-on Kubernetes production experience (microservices, Celery workers, CronJobs, HPAs) and implemented GitOps/CI-CD using GitHub Actions, Docker, and ArgoCD, including moving deployments from on-prem to Azure.”
Aswath Senthilkumar
Junior Full-Stack & ML Engineer specializing in AI-driven web platforms and healthcare analytics
“Backend-focused engineer who owned an AI mentoring workflow platform built in Django with LangGraph multi-agent orchestration, optimizing it to stay under 200ms latency while scaling past 1,200 active users using profiling, caching, load testing, and OpenTelemetry-style tracing. Also has hands-on experience containerizing and deploying Python/ML services to AWS ECS via GitHub Actions/GitOps, and building reliable real-time pipelines with webhooks and Redis queues (idempotency, backpressure, DLQ).”
Saharsha Goud
Senior Full-Stack Java Developer specializing in microservices and cloud platforms
“Full-stack engineer focused on data-heavy platforms, building Spring Boot microservices and Angular/React dashboards end-to-end. Has hands-on experience improving large-scale API and UI performance (including cutting 8–10s response times) and ensuring cross-service consistency using Kafka, idempotent consumers, and strong validation/transaction patterns on AWS with CI/CD and observability (Prometheus/ELK).”
Althaf Shaik
Senior Software Engineer specializing in cloud-scale distributed systems and data platforms
“LLM/RAG-focused engineer who repeatedly takes agentic workflows from impressive demos to dependable production using rigorous evals, SLOs, and deep observability. Has led high-impact incident mitigation (22-minute MTTR during a major sale) and developer enablement workshops, and partnered with sales to close a $410k ARR enterprise deal with a tailored RAG pilot (FastAPI/pgvector/Okta/InfoSec-ready).”
Satya VM
Mid-level GenAI/Data Engineer specializing in LLMs, RAG systems, and fraud detection
“ML/NLP engineer with banking domain experience who built a GenAI-powered fraud detection and risk intelligence system at Origin Bank, combining RAG (LangChain + FAISS), fine-tuned BERT NER, and GPT-4/Sentence-BERT embeddings. Delivered measurable impact (25% higher fraud detection accuracy, 40% less manual review) and emphasizes production-grade pipelines on AWS SageMaker/Airflow with strong data validation and scalable PySpark processing.”
Shreya Thakur
Mid-level Software Engineer specializing in Python backend and LLM/ML systems
“Backend/AI engineer who has shipped production LLM systems end-to-end, including an AI request-routing service (FastAPI + BART MNLI + OpenAI/Gemini) that improved accuracy ~25% after launch via eval-driven prompt/category iteration. Also built an enterprise document intelligence/RAG platform on Azure (Blob/SharePoint/Teams ingestion, OCR/NLP chunking, embeddings in Azure Cognitive Search) with PII guardrails (Presidio), confidence gating, and scalable event-driven pipelines handling millions of documents.”
Nandakumar Punniakoti
Mid-Level Full-Stack Product Engineer specializing in TypeScript/React, Java, and AI integration
“Full-stack product engineer who builds and owns production features across Next.js/React/TypeScript and Java Spring Boot, with strong Postgres data modeling and performance tuning. Has delivered measurable improvements (60%+ faster renders, 2s→100ms queries, 50% lower workflow latency) and built reliable Kafka-based workflows with robust observability (Prometheus/Grafana/Alertmanager) and high test coverage.”
Raghavendra Dubey
Mid-level Software Engineer specializing in Java microservices and cloud-native systems
“Enterprise workflow/product engineer (DXC) who owned a customer-facing workflow application for 500+ users and improved performance ~30% through API/SQL optimization, caching, and CI/CD-backed iteration. Experienced designing React/TypeScript + Java/Spring Boot systems and operating microservices with RabbitMQ/Kafka-style messaging, emphasizing reliability via DLQs, backpressure, and strong observability. Also built an internal automation dashboard adopted by support/ops teams to cut manual work and reduce SLA misses.”
Rasega Babu Kavitha
Mid-Level Full-Stack Software Engineer specializing in Java/Spring and React
“Full-stack engineer who has shipped a real-time social engagement feature (live messaging + personalized feeds) for a career networking platform, owning everything from WebSockets/SSE and JWT+Redis auth through Docker/Kubernetes production deployment. Also built a production Flask backend for an AI-driven movie recommendation system on AWS, with strong API design (versioning/error standards) and hands-on performance tuning (Typesense +47% query improvement, Postgres indexing, Redis caching, CloudWatch-driven incident response).”
Likhith Kumar Yaramala
Junior Backend/Cloud Software Engineer specializing in microservices and DevOps
“Cloud/DevOps-focused engineer with strong Linux production operations experience, deploying microservices to AWS on Docker/Kubernetes. Has built and operated secure CI/CD (GitHub Actions/Jenkins) and Terraform IaC workflows with approvals, remote state, and drift detection, and has hands-on incident recovery experience in containerized environments; limited direct IBM Power/AIX/PowerHA exposure.”
John Kalyango
Senior Full-Stack Software Engineer specializing in geospatial and mobile data collection
“Frontend engineer who led end-to-end development of a React-based carbon credits data collection and analysis tool, focusing on scalable architecture and performance (code splitting, SWR caching, memoization, Lighthouse monitoring). Experienced building complex route-driven TypeScript wizards with Redux/Rematch state persistence, and refactoring legacy monolithic UI into reusable, tested, documented components while shipping deadline-driven features using feature flags and tight QA collaboration.”
Muhammad Waqas Ashraf
Senior Full-Stack Engineer specializing in AI, cloud infrastructure, and DevOps
“Frontend engineer focused on building and scaling data-heavy, real-time dashboards with React/Next.js/TypeScript. Emphasizes performance and reliability at scale through modular architecture, centralized state (Zustand/Redux), strict API contracts, automated testing, and production monitoring (Grafana/CloudWatch), and has experience shipping quickly with feature-flagged rollouts and rapid iteration from user feedback.”
Ankush Desai
Junior Robotics Engineer specializing in ROS, perception, and robotic manipulation
“Robotics software engineer focused on ROS2 autonomy stacks, with hands-on work spanning semantic 3D SLAM, sensor fusion, and controller customization. Built an indoor GPS-denied semantic SLAM system (>95% accuracy) and extended Nav2’s MPPI controller with a custom C++ critic to keep an agricultural rover centered in crop rows, boosting CO2 laser weeding effectiveness by 40%. Strong in simulation-to-real workflows (Isaac Sim, Gazebo Ignition) and deployment automation (Docker on Jetson Orin NX, GitHub Actions CI/CD).”
Ashritha G
Mid-Level Software Development Engineer specializing in distributed systems and cloud microservices
“Software engineer with enterprise, customer-facing delivery experience across Outlier AI and Wipro—builds and productionizes workflow and integration solutions with a strong focus on real-world performance and reliability. Delivered a Firestore/Redis-backed real-time pipeline that cut page load times by 20% and held consistent performance across 10,000+ sessions, and has hands-on production incident experience stabilizing high-traffic microservices via caching, indexing, and safe canary deployments.”
Sam Fish
Senior Full-Stack Engineer specializing in web platforms, cloud infrastructure, and data systems
“Full-stack/product-leaning engineer who owned an end-to-end AI Tutor feature (Claude-powered) shipped simultaneously to iOS/Android/web via Expo, with Cloudflare Workers backend and PostHog analytics. Built the company’s GitHub-based CI/CD to coordinate app store releases with backend blue/green deployments. Also has significant data engineering experience (including ~8TB/day workloads) using dbt/Fivetran plus sharding and hashing-based diffing for correctness.”
Abhishek Ingle
Junior Full-Stack & AI Software Engineer specializing in React/Next.js and LLM systems
“Backend engineer with hands-on experience building low-latency, high-concurrency real-time chat on AWS (Node.js/Socket.IO/MongoDB) and improving reliability under unstable networks, contributing to ~40% user adoption growth. Also built FastAPI-based AI assistant context retrieval (RAG) APIs with embeddings/vector search, and has strong production experience in rate-limit handling, async refactors with safe rollout, and Supabase Auth/RLS optimization.”
Owen Wolff
Junior Software Engineer specializing in full-stack web and systems programming
“Junior engineer who built a novel, highly-performant database explorer at Electric Capital: a TypeScript/React UI backed by Zig-compiled WebAssembly that loads data locally for fast filtering/sorting and responsive lazy loading, with CI/CD and Cloudflare-based auth. Also led graphics work on a WebGPU browser game engine capstone, creating TypeScript abstractions over WGSL/shader and GPU buffer complexity to accelerate teammates.”
Jaykumar Kotiya
Mid-level Machine Learning & AI Engineer specializing in Generative AI, NLP, and MLOps
“Built and deployed production LLM systems for summarizing sensitive legal and financial documents, emphasizing GDPR-aligned privacy controls and scalable hybrid cloud architecture. Experienced with Kubernetes/Airflow orchestration and rigorous testing/monitoring practices, and has delivered measurable business impact (18% conversion lift) by translating AI outputs for non-technical marketing stakeholders.”
Tracy Nguyen
Mid-Level Software Engineer specializing in Front-End Web Development
“Frontend engineer with React + TypeScript experience building internal dashboards and a nonprofit festival website delivered end-to-end in 6 weeks. Emphasizes scalable quality practices (documentation ownership, code reviews, CI/CD, testing) and user-centered delivery, including accessibility, multilingual support, and enabling non-technical stakeholders to update content.”
Kingsley Torlowei
Senior Software Engineer specializing in AI systems and data platforms
“Built and productionized LLM agents that ingest multi-source workplace data (Slack, meetings, calendars, PM tools) to extract entities (tasks/decisions/risks/initiatives) and generate customer insights like risk alerts, deadline-miss prediction with evidence, and workload overload detection. Also architected a graph-DB-backed multi-step agent using LangChain + Pydantic with async queue/worker execution and LLM-as-judge evaluation plus human review loops.”