Vetted GitHub Actions Professionals

Kiran M

Screened

Mid-Level Full-Stack Software Engineer specializing in cloud-native microservices and data platforms

Bentonville, AR5y exp

“Backend/ML integration engineer with experience at Accenture and Walmart building Flask-based analytics and prediction APIs on PostgreSQL/MySQL. Strong focus on performance and scalability—uses precomputed aggregates, Redis caching, query tuning (indexes/partitioning/EXPLAIN), and async/background processing; also designs secure multi-tenant isolation with JWT and schema/db-per-tenant strategies.”

Shruthi Nandakumar

Screened

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

St. Louis, MO5y exp

“Backend/AI engineer who owned a high-scale Java/Spring Boot microservice for a financial application (millions of requests/day) and led major reliability/performance fixes (including ORM/query and PostgreSQL tuning) achieving ~60% latency reduction. Also shipped application-layer LLM features for ops teams (summarization + tool-calling) with strong guardrails (PII redaction, validation, audit/feedback) and designed a state-driven agent workflow with retries, circuit breakers, and human escalation.”

Keerthi Kalluri

Screened

Senior Full-Stack & GenAI Engineer specializing in healthcare and financial services

6y exp

“Built and deployed a production LLM-powered customer support assistant using a RAG backend in Python, focused on deflecting repetitive Tier-1 tickets and reducing resolution time. Demonstrates strong production engineering instincts around reliability (confidence scoring + human fallback), scalability/cost optimization (multi-stage pipelines), and workflow orchestration/observability (LangChain, custom DAGs, structured logging, step metrics).”

Niharika Bhasin

Screened

Intern Full-Stack Software Engineer specializing in AWS serverless and real-time web apps

New York City, NY0y exp

“New-grad/early-career engineer who led high-stakes modernization of a field-operations platform from Firebase to AWS using an incremental/dual-write strategy, achieving zero downtime and ~30–32% infra cost reduction while improving scalability. Also built and productionized an AI-native code assistant (LangChain + Pinecone RAG) with measurable online metrics and safety guardrails, and has experience working directly with CEO/CTO/CPO and embedded with customer teams to ship enterprise features quickly.”

Nikitha Margadi

Screened

Mid-level Data Engineer specializing in cloud lakehouse, streaming, and MLOps

Texas, USA5y exp

“Data engineer at AT&T focused on large-scale telecom (5G/IoT) data platforms, owning end-to-end pipelines from Kafka/Azure ingestion through Databricks/Delta Lake transformations to serving analytics and ML. Has operated at very high volumes (~50+ TB/day) and delivered measurable performance gains (25–30% faster processing) plus improved reliability via Airflow monitoring, robust data quality checks, and resilient external data collection patterns (rate limiting, retries, dynamic schemas).”

Nikhitha santhoshi Maroju

Screened

Mid-level Full-Stack Software Engineer specializing in Java/Spring microservices on AWS

Redwood, CA4y exp

“Built and shipped a production LLM-powered fraud investigation agent using RAG to generate transaction explanations and draft analyst reports. Emphasizes production robustness (fallbacks, strict structured outputs, async orchestration, monitoring/evals) and reports measurable impact: ~12% precision lift and ~80 high-priority alerts per week with reduced manual effort.”

“Platform/infrastructure engineer with hands-on ownership of Kubernetes, Terraform, VMware, and hybrid on-prem/AWS environments. Stands out for combining deep platform build/upgrade experience with strong incident response and reliability practices, including a Terraform redesign at H&R Block that reduced provisioning time by 40% and hybrid networking improvements that hardened Direct Connect failover.”

Yuchen Wang

Screened

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

New York, NY1y exp

“Built and maintains an AI Finance Tracker end-to-end as a solo full-stack product owner, from Figma designs and React frontend to Flask APIs, Firestore, auth, deployment, and AI insights. Stands out for combining product instinct with pragmatic engineering decisions like pre-aggregating financial data to control LLM costs and adding OCR receipt scanning based on real user feedback.”

“ML/AI engineer focused on taking LLM products from experiment to production, with hands-on ownership of a RAG-based customer support system that improved response quality by 35% and cut latency by 30%. Stands out for combining product impact with production rigor across retrieval tuning, safety guardrails, monitoring, and reusable Python/FastAPI services that accelerated adoption across teams.”

Brendan Dwyer

Screened

Senior AI/ML Engineer specializing in GenAI and cloud platforms

Colorado Springs, CO10y exp

“ML/AI engineer with hands-on experience turning research-style RAG concepts into production underwriting systems at Prudential Financial. Built an internal document intelligence assistant end-to-end with strong monitoring, safety, and evaluation practices, driving a 38% faster review process and 31% better retrieval accuracy. Also improved platform engineering at VivSoft by standardizing Python-based ML deployment across 60+ models.”

Paavani Karuturi

Screened

Junior Backend and ML Engineer specializing in distributed systems and LLM infrastructure

San Jose, CA2y exp

“Backend engineer with strong ownership across authentication, API infrastructure, and AI-powered document workflows. They built and operated a production auth microservice supporting 10,000+ users with measurable latency and security improvements, and also shipped hackathon and applied-AI systems including legal document and medical document retrieval/Q&A products.”

Sai Sreenath Kalva

Screened

Mid-level Full-Stack Software Engineer specializing in AI and Healthcare IT

Rosemead, CA5y exp

“Full-stack engineer with strong AI architecture experience in regulated healthcare environments, including a HIPAA-compliant conversational reporting assistant for LA County Department of Public Health and clinical workflow features for Oracle Health/Cerner PowerChart. Stands out for combining LLM/RAG system design, healthcare compliance, and production-grade reliability practices across Azure, AWS, and Kubernetes.”

Sriram Degala

Screened

Senior AI/ML Engineer specializing in healthcare and finance AI

Dallas, TX4y exp

“Built production-grade medical AI systems at MD Anderson, including an end-to-end RAG chatbot used by clinical researchers for real-time drug interaction and trial literature queries. Stands out for combining healthcare domain knowledge with strong MLOps, evaluation, and safety practices, and for delivering measurable gains in latency, retrieval precision, and team adoption.”

“Software engineer with 4 years of experience spanning scalable backend systems, full-stack product development, and production LLM integrations in finance, insurance, and e-commerce contexts. They describe shipping an AI-powered internal financial analysis tool, improving document-review workflows by 40%, and driving a zero-to-one B2B SaaS subscription launch with cross-functional GTM alignment.”

“Full-stack engineer at an early-stage startup with hands-on production experience spanning Angular frontend features, backend safety checks for an image-generation workflow (OpenAI Safety), and AWS operations. Built CI/CD to ECS with GitHub Actions, implemented CloudWatch observability, and improved release reliability via Blue/Green deployments with automatic rollback.”

“Backend engineer in healthcare data systems who has owned production pipelines end-to-end, from ingesting patient and claims data to serving it through secure APIs. Brings a strong mix of Python, SQL, microservices, cloud deployment, and data reliability practices, with measurable performance gains and experience building resilient integrations with external data sources.”

“Frontend-leaning full-stack engineer with experience building real-time, high-stakes operational software for airport gate management and billing/analytics systems. Stands out for combining strong React/TypeScript architecture with backend and data-layer ownership, including WebSockets, SQL optimization, and analytics feature delivery in production.”

VINAY KUMAR VIPPALA

Screened

Mid-level Software Engineer specializing in FinTech backend systems

Seattle, WA5y exp

“Full-stack product engineer with hands-on ownership from React UI through Spring Boot APIs and SQL data layers, focused on transaction-heavy fintech workflows. Built both a transaction reconciliation system and a 0-to-1 AI-based anomaly detection workflow at LeisurePay, combining performance-minded frontend engineering with pragmatic product delivery.”

Apoorva Swaminathan Iyer

Screened

Mid-level Software Developer specializing in full-stack engineering and application security

Raleigh, NC3y exp

“Developer who has evolved into an AI-native builder, using Claude, Copilot, Cursor, and multi-agent workflows as collaborators while retaining ownership of architecture and code quality. At OpenPRA, they ramped quickly into NestJS from a Spring Boot background and implemented OAuth/JWT security; on the Aha quiz app, they effectively acted as a tech lead for AI agents across feature delivery, debugging, CI/CD, and Dockerization.”

“Full-stack software engineer who has owned production workflows spanning React/Next.js, FastAPI, Redis-backed async processing, and PostgreSQL in a multi-tenant invoice-processing product. Shows strong product instincts as well—improving UX for long-running operations, iterating MVPs based on real user behavior, and balancing reusable abstractions with practical implementation constraints.”

“Founding engineer at an edtech startup who combines hands-on engineering leadership with advanced AI-native development workflows. They’ve built an AI grading pipeline and a multi-agent SDLC tool, and stand out for treating AI agents like an engineering team with planning, parallel execution, QA, and rigorous validation.”

Michael Boaz

Screened

Senior Software Developer specializing in cloud-native and event-driven architecture

Atlanta, GA24y exp

“Built and shipped production LLM/agent systems on AWS for internal developer support and IT observability use cases, including a Claude-based support tool grounded in internal documentation and a cost-optimized ServiceNow integration. Stands out for combining agent design, cloud architecture, CI/CD, chaos testing, and observability to make non-deterministic systems reliable and maintainable in production.”

“Full-stack engineer focused on AI-powered enterprise document automation, especially transforming unstructured financial documents into structured outputs. Stands out for treating LLMs and agents as components within robust production systems, with emphasis on validation, security, observability, and scalable multi-agent architecture.”

“Engineering leader with 8+ years across IoT, emergency messaging, and political campaign data science, including operating a massive IoT microservices platform at several million devices and roughly 200 million requests per minute. Particularly strong in retrofitting legacy systems for modern observability using OpenTelemetry, Honeycomb, and Grafana LGTM, while also managing distributed international teams and developing engineers into senior and tech lead roles.”