Vetted GitHub Actions Professionals

“Backend/full-stack engineer with Blue Cross Blue Shield experience building a reactive, event-driven claims processing microservice platform on AWS (ECS, SNS/SQS) with Terraform-based IaC and strong observability (Dynatrace/CloudWatch). Demonstrated measurable production impact (32% less downtime, 24% higher processing efficiency) and deep database performance/migration expertise across MongoDB and Postgres.”

Supreet Purthpli

Screened

Mid-level AI/ML Software Engineer specializing in cloud-native MLOps and FinTech

San Francisco, CA4y exp

“Software engineer with JPMorgan Chase experience delivering end-to-end fintech features (Next.js/React/Node/Postgres on AWS) and measurable performance gains. Built and productionized an AI-native credit decisioning workflow combining LLMs, vector retrieval, and a rules engine with strong governance (bias checks, auditability, human-in-loop), improving precision and cutting underwriting turnaround time by 40%.”

Ajay Desai

Screened

Mid-level Full-Stack Software Engineer specializing in FinTech and backend platforms

USA4y exp

“Built an AI-native legal research platform that automated analysis across 100,000+ dense legal documents, combining LLM workflows, async backend architecture, and conversational retrieval in production. Also brings cross-domain experience in investment-analysis agents and healthcare claims/billing systems, with a strong emphasis on reliability, deterministic orchestration, and safe handling of messy operational data.”

Dikshith Pulakanti

Screened

Intern AI Engineer specializing in agentic LLM systems

Singapore, Singapore0y exp

“Built multiple AI-heavy backend systems from scratch, including FORESIGHT, a personal financial intelligence platform running daily on live bank accounts with zero manual intervention, and JobPilot, an autonomous job application agent spanning Workday, Greenhouse, Lever, and custom forms. Stands out for combining strong systems design with applied ML pragmatism, reproducibility, and unusually candid reflection on security, scalability, and observability tradeoffs.”

“Backend/AI engineer who has owned production agentic systems end-to-end, including a CRM-integrated multi-agent financial workflow at Wow Payments that cut latency by 83% and achieved 98% uptime. Also built an AI real estate product ('Site IQ') by turning vague stakeholder goals into a geospatial autonomous agent using RAG, rapid prototyping, and tight validation layers around GPT-4 outputs.”

“Frontend-focused engineer at YTech Global with roughly 3.5 years on a logistics contract management platform, owning major pieces of architecture for micro frontends, real-time workflows, and operational dashboards. They describe building the first UI-based contract management experience for shippers and carriers, helping grow usage from 10,000 to 20,000 users while partnering closely with backend teams on API and WebSocket design.”

“Front-end engineer with experience building high-stakes internal products in financial services at Visa and Wells Fargo. They combine deep browser-performance knowledge with pragmatic typed architecture and close user observation, delivering measurable outcomes like cutting AML case resolution from 12 days to 4 and improving trader alert response through data-driven UI changes.”

Sanket Mungikar

Screened

Mid-level Software Engineer specializing in distributed backend and AI analytics platforms

California, USA4y exp

“Full-stack engineer at BigCommerce who combines customer-facing deployment ownership with hands-on AI/LLM systems work. Built and launched merchant analytics and predictive inventory workflows using React, TypeScript, FastAPI, Kafka, AWS, and RAG-style architectures, and has real production experience debugging non-deterministic AI issues caused by data pipeline freshness and event-ordering problems.”

Sai Divya Mulukala

Screened

Mid-level Full-Stack Software Engineer specializing in FinTech and distributed systems

USA5y exp

“Full-stack engineer with experience building operational dashboards at Walmart and improving digital banking experiences at Bank of America. Stands out for tracing performance issues across frontend, APIs, and backend services, including cutting response times from 1.2s to 700ms and resolving duplicate event-processing problems in distributed systems.”

“AI/full-stack engineer with experience spanning startup product building at Twinly, enterprise analytics at Zoho, and high-stakes life sciences ML at Wave Life Sciences. Stands out for combining React/TypeScript + FastAPI product execution with rigorous AI evaluation, retrieval optimization, and human-in-the-loop design, delivering measurable outcomes like 75% fewer analytics requests, 20% fewer failed experiments, and MVP delivery 3 weeks early.”

Nithyashree Raghunathan

Screened

Mid-level Full-Stack AI Engineer specializing in agentic systems

Santa Clara, CA5y exp

“QA/data pipeline engineer with hands-on AI product building experience, spanning enterprise AWS migration testing for Belgium postal services and personal multi-agent systems in fintech and recruiting. Stands out for combining rigorous validation and production stability work with modern LLM orchestration, guardrails, and messy-document normalization workflows.”

“Full-stack product engineer who has built both operational systems and enterprise AI copilots in production. They owned an AI-powered inventory platform end-to-end, driving a 45% drop in stock issues, and also shipped a Microsoft Teams-based HR/IT copilot using RAG and workflow automation that reduced repetitive support queries by roughly 30%.”

“Product leader with experience rebuilding teams and platforms in both healthcare and AI-enabled SaaS environments. Most notably rebuilt Uniform Teeth’s product organization, EMR, and patient app after a restructuring, contributing to major clinical efficiency gains and the company’s acquisition by Impress in 2022. Brings a strong human-in-the-loop AI philosophy, plus experience leading PMs, design, and engineering through high-change environments.”

“Built an internal AI-powered document search and Q&A platform at BNY that let employees query company documents in natural language and get grounded answers in seconds. Brings practical full-stack and LLM systems experience across React/TypeScript, FastAPI, Pinecone, OpenAI, and Claude, with clear emphasis on retrieval quality, hallucination reduction, and production monitoring.”

“Platform/DevSecOps engineer who combines full-stack product ownership with practical LLM systems in production. They built a self-service secrets management portal that reduced DevOps bottlenecks while maintaining compliance, and shipped AI-powered deployment debugging and security-remediation workflows with strong guardrails, monitoring, and human-in-the-loop controls.”

rajasri mamidi

Screened

Mid-level Frontend Engineer specializing in FinTech web applications

Jersey City, NJ5y exp

“Frontend-leaning product engineer with strong end-to-end ownership across AI support and real-time observability products. They combine React/TypeScript architecture depth with backend/API collaboration, deployment ownership, and measurable impact, including a 40% reduction in support-agent lookup time.”

“Built and owned an AI-powered real-time financial fraud detection and monitoring platform end-to-end, spanning product decisions, backend architecture, frontend dashboards, deployment, and production support. Their work scaled to 120M transactions/day and materially improved fraud detection accuracy from 78% to 94%, showing rare breadth across distributed systems, observability, and React-based operational analytics.”

“Backend engineer who designed and evolved an AWS-based event-processing system in Python/PostgreSQL, achieving a 60% p95 latency reduction while improving reliability during traffic spikes. Led a zero-downtime migration from a monolithic Django app to FastAPI microservices using feature flags, strong testing, and cross-team coordination, with production-grade observability (Prometheus/Grafana/CloudWatch) and security (JWT/OAuth2, RBAC, Postgres RLS).”

“Robotics/AV engineer with strong ROS2 and autonomy stack integration experience, including bringing Autoware Universe up on a real Lexus autonomous vehicle platform. Also built a hierarchical reinforcement learning proof-of-concept for Boston Dynamics Spot (navigation + manipulation) and tackled sim-to-real challenges by implementing PD torque conversion for Jetson-based hardware; improved localization accuracy via GNSS+EKF fusion with a reported 28% drift reduction.”

“Backend/data engineer who builds production FastAPI microservices and AWS serverless/Glue pipelines for SMS analytics and marketing segmentation. Led a legacy batch modernization into modular services (FastAPI + Glue/Athena + ClickHouse) using shadow-mode parity checks, feature flags, and incremental rollout. Demonstrated measurable performance wins (12s to sub-second SQL; ~40% CPU reduction) and strong incident ownership with proactive schema-drift prevention.”

“Robotics/ROS2-focused early-career engineer who built a stereo visual-odometry SLAM system for autonomous navigation and optimized it to run reliably in real time on Raspberry Pi. Strong in sensor fusion (camera+IMU), ROS2 debugging/profiling, and distributed robotics/IoT pipelines (ROS2 + MQTT + cloud), with added experience extracting WiFi CSI for sensing/localization and shipping via Docker + GitHub Actions CI/CD.”

“Built a web-based online Sudoku game in JavaScript (multiplayer format supporting up to 6 teams with up to 5 players each) and demonstrates strong product/analytics orientation. Uses a KPI-driven approach (DAU/WAU, ARPU, session duration, LTV) and structured prioritization methods (MoSCoW, story mapping, cost of delay, DFV) to iterate toward targets; seeking a remote role around $70k/year.”

“Backend engineer who has built high-throughput analytics and fraud-detection systems, combining Python/Flask + Celery/RabbitMQ with strong PostgreSQL performance tuning (indexing, partitioning, EXPLAIN ANALYZE). Has production experience integrating ML inference (scikit-learn/TensorFlow → TensorFlow Lite) into Spring Boot microservices with caching and model versioning, plus designing secure multi-tenant architectures using JWT-based tenant routing and PostgreSQL RBAC/RLS.”

“Master’s-in-Data-Science candidate (UHV) with 4+ years in AI engineering building production LLM and multimodal systems. Designed an LLM-powered workflow automation platform using RAG over vector stores with guardrails (schema/output validation, fallbacks) and a rigorous evaluation/monitoring framework including drift tracking and shadow deployments. Experienced orchestrating large-scale vision-language pipelines with Airflow and Kubernetes (OCR, distributed training) and partnering with non-technical ops stakeholders to cut cycle time and reduce errors.”