Vetted GitHub Actions Professionals

“ML/AI engineer with production experience at S&P Global and Accenture, focused on regulated, enterprise-grade systems. Built end-to-end financial risk and credit default models with >90% precision and 12% fewer false positives, and is currently developing secure RAG pipelines on AWS SageMaker for enterprise insight extraction.”

“ML/AI engineer at PNC who has shipped enterprise-grade RAG and document intelligence systems for compliance and policy workflows. Stands out for combining LLM product thinking with production rigor—owning FastAPI/Kubernetes deployments, monitoring, evaluation, and human-feedback loops that drove measurable gains like 40% faster policy search and 30% faster compliance review.”

premkumar narla

Screened

Mid-level AI/ML Engineer specializing in GenAI, RAG, and enterprise ML systems

Chicago, IL5y exp

“ML/AI engineer with hands-on experience at Morgan Stanley building production fraud detection and enterprise RAG systems. Stands out for owning systems end-to-end—from experimentation and deployment to monitoring and iteration—and for delivering measurable impact, including an 18% reduction in fraud false positives, 40% lower inference latency, and internal tooling that reduced model deployment time from days to hours.”

“Built and owned an enterprise LLM/RAG document intelligence platform for PNC Financial Services in a compliance-heavy environment, focused on grounded answers over internal finance and policy documents. Stands out for combining GenAI product delivery with production engineering discipline, delivering 60% faster document review and materially better answer quality while creating reusable FastAPI-based AI services for multiple teams.”

Sangita Satapathy

Screened

Senior Full-Stack Engineer specializing in FinTech and AI applications

Las Vegas, NV11y exp

“Engineer with a pragmatic, production-focused approach to AI development, using tools like Copilot and ChatGPT to accelerate coding while maintaining strong engineering fundamentals. Has led a RAG-based multi-stage AI solution spanning retrieval, context building, and response generation, with an emphasis on validation, prompt quality, and reliability.”

“Software developer with a one-year Philips co-op who has already applied AI-assisted coding in production, not just side projects. Stands out for using multi-agent development setups with task-specific sub-agents and a clear human-led orchestration philosophy focused on context, quality control, and security.”

“Built Nexthire-AI, shipping an end-to-end LLM-powered resume–job description matching product (React + Node.js) using embeddings and retrieval to generate match scores and skill-gap recommendations. Improved post-launch engagement by making feedback cleaner and more actionable, and added production guardrails (validation, timeouts, fallbacks) to handle messy resume formats and AI API instability.”

Omkar Lahurikar

Screened

Senior engineering founder specializing in AI systems and automotive controls

Dearborn, MI13y exp

“Builder-minded founder/operator currently at Ford who previously co-founded MeruDynamics, an "Uber for manufacturing" platform, and took it from zero to paying customer without raising capital. He also independently built and deployed RDD, an AI copilot for engineering decision capture, with evals, prompt versioning, and LLM cost telemetry—showing unusual depth in both product thinking and practical AI execution.”

“Engineer with a process-driven approach to AI-assisted software development, focused on orchestrating where AI adds value while maintaining human review and verification. Has applied this in backend work such as an S3-based invoice pipeline and used multi-agent workflows to speed up large API refactors across many endpoints.”

“Backend-focused engineer who uses AI tools pragmatically for rapid development while staying deeply attentive to concurrency, deadlocks, and system reliability. Built foundational AI retrieval architecture for MastadonTutorAI using ChromaDB and RAG pipelines, and is especially interested in applying multi-agent systems to automate complex backend testing and root-cause analysis.”

Siva Harini Sri Janaki Raman

Screened

Mid-level Data Engineer specializing in cloud data platforms

Dallas, TX3y exp

“Built an AI-powered internal support assistant at CVS Health using GPT-4, LangChain, and Pinecone, applying RAG, validation, and monitoring to reduce repetitive support tickets while protecting sensitive healthcare data. Stands out for a pragmatic approach to AI engineering: using multi-agent and LLM workflows to accelerate development while keeping systems constrained, observable, and production-friendly.”

“LLM/agentic systems practitioner who specializes in moving demo-only assistants into reliable, observable, cost-controlled production services. Strong in real-time diagnosis of complex agent workflows (including tracing, loop detection, and guardrails) and in customer-facing enablement—running workshops, building tailored PoCs, and partnering with sales to close deals by proving reliability in high-risk pilots.”

“Backend/platform engineer who has owned a Python/FastAPI results API and deployed it on Kubernetes with Helm and GitHub Actions-driven CI/CD. Demonstrates strong production operations mindset across performance tuning, monitoring, safe rollouts/rollbacks, and phased migrations, plus hands-on Kafka streaming experience focused on ordering and idempotency.”

Anudeep Eloori

Screened

Mid-level Software Developer specializing in full-stack enterprise applications

USA3y exp

“Software engineer with experience building and iterating high-volume Spring Boot microservices on AWS (Docker/Kubernetes) and integrating with React front-ends. Also delivered an LLM-powered document summarization system using embeddings + retrieval (RAG) with grounding/guardrails and built evaluation loops that directly drove retrieval and chunking improvements. Has scaled Kafka-based pipelines processing millions of messy financial/infrastructure records with reliability and cost/latency tradeoff management.”

“Backend-oriented software engineer who uses AI as a disciplined engineering accelerator rather than a replacement for judgment. They have hands-on experience coordinating multiple AI tools/agents across code generation, testing, debugging, and review, with strong emphasis on security, scalability, and human validation before production use.”

Aditya Rao

Screened

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

San Jose, CA5y exp

“Software engineer with 4.5 years of startup experience across programmatic advertising, health tech e-commerce, and automobile diagnostics, plus both bachelor's and master's degrees in CSE. Built an agentic global supply chain platform in a hackathon using a highly structured AI-first workflow, and has hands-on experience designing multi-agent debate systems, rollout safeguards, and observability-driven production fixes.”

“AI automations intern at a lean US-based marketing agency who works directly with founders and builds practical GTM systems end-to-end. He combines ML/LLM tooling with outbound execution, including a clustering-based recommender that improved client lead generation by 30% in two weeks and a personal cold outreach engine that achieved a 12%+ reply rate.”

“Senior software developer with hands-on experience building real-time React + TypeScript dashboards and map-based visualization tools for large datasets. Stands out for practical frontend performance work in production, including memoization, virtualization, debouncing, lazy loading, and Google Maps optimization for thousands of records or points.”

“Built internal product features at Sysco's Collab Cafe across React/TypeScript frontend and Spring Boot/PostgreSQL backend, including a full project invite flow and an early AI-style project matching capability. Stands out for owning features end-to-end, improving React dashboard performance with profiling and component refactoring, and making pragmatic 0→1 tradeoffs to ship quickly.”

Vinay K Naidu

Screened

Senior Full-Stack Engineer specializing in Healthcare IT and FinTech

5y exp

“Built and shipped a production LLM-powered incident assistant integrated with monitoring, logs, and metrics systems that reduced triage time by 30–40% and improved MTTR. Stands out for a strong reliability-first approach to agent design, including deterministic orchestration, strict schemas, fallback flows, grounding checks, and safeguards for messy operational data.”

“Series A startup engineer with broad full-stack ownership across backend, data, and frontend, including a real-time ingestion platform that scaled to 10x higher daily volume without downtime while cutting latency from minutes to seconds. Brings strong fintech and B2B SaaS experience building auditable, high-throughput systems for analysts, operations, and compliance teams in regulated environments.”

“Frontend engineer with production experience at UWM and Ford.com, focused on complex UI architecture, dynamic form systems, and high-performance interactive experiences. Stands out for rebuilding problematic React/Redux patterns into reactive RxJS-driven architectures, with measurable wins like reducing an 8-second, 5,000-request widget to a fast, stable experience, and for also building advanced personal projects in Solid.js, mapping, and WebGL.”

Priyadarshini Vykuntapu

Screened

Mid-level Software Developer specializing in full-stack systems for FinTech and industrial platforms

USA3y exp

“Enterprise full-stack engineer with experience at Honeywell and Wells Fargo, spanning real-time telemetry dashboards and digital banking systems. Stands out for owning production systems end to end, improving performance in high-scale environments, and driving architectural modernization that reduced release times and improved reliability.”

Katha Naik

Screened

Intern software engineer specializing in AI, cloud, and full-stack systems

Fremont, CA2y exp

“Engineer with experience at Fox Corporation and Qualcomm, focused on production automation and AI-powered systems. At Fox, they built a serverless Bedrock Operations CoPilot for broadcast/media operations that centralized fragmented operational data and cut incident investigation time by 50-60% across distributed teams and stations. They also bring applied LLM experience from Qualcomm, where they worked on a safer RAG-based learning assistant for children with autism spectrum disorder.”