Vetted GitHub Actions Professionals

Pre-screened and vetted.

CB

Colin Buckley

Screened

Senior Software Engineer specializing in systems, infrastructure, and defense R&D

Columbus, OH10y exp
BattelleGeorge Mason University

Engineer working in a venture-studio-style company that spins up SaaS products and new businesses, often owning early product and technical direction across teams ranging from 1 to 100 people. Particularly strong at hardware-software systems: they led software design and hardware choices for a 360 vision product and built a company-wide HIL testing platform with Go/Python/TypeScript, multi-language SDKs, and flexible endpoint architecture.

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Adam Sandler - Senior Full-Stack Engineer specializing in Python web platforms

Adam Sandler

Screened

Senior Full-Stack Engineer specializing in Python web platforms

7y exp
ByteSparklesUC Berkeley

Full-stack engineer with strong Python and React/TypeScript experience who has worked in lean startup environments on B2B SaaS hiring platforms. Most notably, they drove redesign work on developer search and matching systems at G2i, combining product collaboration, backend architecture, and database/query optimization to improve match quality and keep search responses around 100ms at scale.

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HR

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

Virginia, USA5y exp
Amazon Web ServicesUniversity of Maryland, Baltimore County

Full-stack engineer with hands-on ownership of a customer-facing advanced performance metrics experience in the Amazon S3 console, spanning React UI, Python/Node services, Redshift/RDS data access, and AWS IaC/CI-CD with CloudWatch/Route53 operational readiness. Demonstrates strong production instincts around resilience (partial failures, multi-region inconsistencies), progressive rollouts/feature flags, and reliable ETL/integration patterns (idempotency, backfills, reconciliation).

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KG

Kajal Gada

Screened

Senior Robotics Software Engineer specializing in ROS, CI/CD, and autonomy tooling

Boston, MA7y exp
Boston Dynamics AI InstituteUniversity of Maryland, A. James Clark School of Engineering

Robotics software engineer with hands-on experience migrating a robotics project from ARM to AMD by building a Dockerized environment with PyTorch/CUDA dependencies, improving data processing and battery efficiency. Has integrated ROS 2 nodes for a Time-of-Flight camera and debugged motion-planning issues (tight-turn stopping) using data collection and iterative tuning; also built custom robots in Webots for sensor/actuator-driven behaviors.

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MS

Manvir Singh

Screened

Senior Full-Stack & Mobile Software Engineer specializing in cloud-based applications

Englewood, NJ10y exp
Cobalt BrandsUniversity of Washington

Data/ML backend engineer with hands-on production experience spanning RAG services (LlamaIndex/OpenAI) and AWS data platforms. Has delivered Terraform-managed AWS architectures (Lambda + ECS Fargate) with secure secrets handling, built Glue-to-Redshift ETL with schema evolution controls, modernized SAS reporting into Python microservices, and achieved major Redshift query speedups (2+ hours to under 15 minutes).

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BD

Mid-level Full-Stack Software Engineer specializing in FinTech microservices

California, USA4y exp
PayPalCalifornia State University, Long Beach

Robotics software engineer who has built end-to-end pipelines spanning backend/data processing through model interfaces and hardware integration. Has hands-on ROS2 experience building Python nodes and debugging real-time behavior via profiling, publish-rate tuning, and latency fixes, plus experience standardizing multi-robot communication with QoS adjustments. Uses Gazebo simulation and Docker/CI/CD to catch integration issues early and speed iteration.

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SM

Mid-level Full-Stack Developer specializing in Java/Spring Boot, React, and cloud-native AI automation

Long Beach, CA3y exp
UberCalifornia State University

Software engineer focused on reliability and scalable systems: built React/TypeScript dashboards backed by Java/Spring Boot APIs and designed Kafka-based microservices with strong contract/versioning discipline. Known for shipping incremental improvements with tight feedback loops and for creating internal observability tools that streamline on-call and incident diagnosis under high-traffic conditions.

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JM

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

Dallas, TX6y exp
Johnson & JohnsonUniversity of North Texas

Full stack engineer in the financial/thematic investing domain who built end-to-end applications on AWS. Notably redesigned a slow portfolio analytics workflow by offloading heavy computations to scheduled AWS Lambda jobs and caching results in DynamoDB (TTL), cutting API latency from ~5 seconds to under 300ms while supporting data-heavy daily market processing.

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AG

Junior Cloud/DevOps Engineer specializing in Kubernetes, Terraform, and multi-cloud customer engineering

New York, NY2y exp
SeqeraUniversity of Waterloo

Solutions Engineer focused on application and platform security for enterprise cloud-native deployments, advising customers on threat modeling and secure CI/CD practices across AWS and Kubernetes. Has implemented SCA/container scanning and vuln checks in pipelines, tuned thresholds to reduce false positives, and driven outcomes like faster security approvals and smoother production rollouts. Troubleshot high-load Kubernetes failures (OOMKills, registry throttling) and turned fixes into a standard tuning guide.

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AS

Mid-level Java Full-Stack Developer specializing in cloud microservices

USA4y exp
PaychexTrine University

Backend/platform engineer with payroll domain depth who built high-volume payroll processing microservices (Java/Spring Boot, Kafka, PostgreSQL, Redis) on AWS Kubernetes and debugged major peak-cycle latency by redesigning transaction boundaries and moving to async Kafka processing (>50% latency reduction). Also shipped an LLM-powered HR assistant using RAG with strong security/guardrails (RBAC, PII masking, audit logs) that cut support tickets by 40%, and designed reliable multi-step agent workflows with retries, circuit breakers, and idempotency.

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TN

Tanveer Nazir

Screened

Senior Cloud & DevOps Engineer specializing in enterprise cloud automation and Kubernetes

Remote, NY11y exp
Bank of AmericaCollege of Staten Island, CUNY

Infrastructure/DevOps engineer with primary ownership in enterprise Linux and AWS/Azure production environments (including financial systems). Built secure, repeatable CI/CD pipelines deploying containerized workloads to EKS/ECS and implemented Terraform/CloudFormation IaC with drift detection and rollback practices; lacks direct IBM Power/AIX/PowerHA experience.

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SP

Mid-level Backend Software Engineer specializing in Python APIs and payment systems

USA6y exp
StripeSouthern Illinois University Carbondale

Backend/ML systems engineer with Stripe payments experience who built an asynchronous processing upgrade handling millions of API requests, cutting peak latency ~20–25% while preserving strict financial consistency via idempotency-safe retries and robust validation/fallbacks. Also built scalable ETL pipelines for messy CSV/Excel/API data with strong observability (structured logging/monitoring) and reliability mechanisms.

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RK

Mid-level AI/ML Engineer specializing in Generative AI, Conversational AI, and RAG systems

NJ, USA4y exp
Scale AIRowan University

Built and shipped a production enterprise RAG knowledge assistant that returns grounded, cited answers and uses confidence-based fallbacks (clarifying questions/abstention) with monitoring and compliance controls for sensitive data. Implemented end-to-end agent orchestration (function calling, structured JSON, state, retries/rate limits) plus eval/feedback loops, and achieved a reported 30–40% improvement in knowledge-task completion time while reducing hallucinations via retrieval improvements.

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Lavanya Chilakalapudi - Mid-level Full-Stack Developer specializing in cloud-native web apps and APIs in Tampa, FL

Mid-level Full-Stack Developer specializing in cloud-native web apps and APIs

Tampa, FL5y exp
DatabricksUniversity of South Florida

Backend engineer with experience building microservice-based systems that integrate LLM workflows (code review suggestions, documentation generation, test scaffolding) using REST APIs, Celery/Redis, and OpenTelemetry for observability. Demonstrates hands-on database and performance optimization in PostgreSQL/SQLAlchemy (bulk inserts, lock mitigation, cursor-based pagination) plus multi-tenant data isolation via tenant-aware models, middleware scoping, and schema/row-level strategies.

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Shobana Chandrasekaran - Mid-Level Software Engineer specializing in AI microservices and generative fashion in Sunnyvale, CA

Mid-Level Software Engineer specializing in AI microservices and generative fashion

Sunnyvale, CA2y exp
The Fword.aiUSC

Backend/AI workflow engineer at a startup building production AI services for fashion workflows, including an AI-powered techpack generation API in Go (Gin) with MongoDB handling ~1k+ daily requests. Recently implementing an image-to-3D dress generation feature end-to-end, integrating a Python FastAPI AI service with ComfyUI + Hunyuan, with strong emphasis on async orchestration, webhooks, and observability (OpenTelemetry + SigNoz).

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Shriya Bannikop - Mid-level Software Engineer specializing in cloud platforms, data engineering, and distributed systems in Seattle, WA

Mid-level Software Engineer specializing in cloud platforms, data engineering, and distributed systems

Seattle, WA5y exp
Amazon Web ServicesKLE Technological University

Full-stack engineer who built and owned an AI-assisted job-matching dashboard in Next.js App Router/TypeScript, keeping LLM logic server-side and improving performance via deduplication, caching/revalidation, and streaming (35% fewer duplicate LLM calls; 40% faster first render). Also has strong data/backend chops: designed Postgres models and optimized queries at million-record scale (1.8s to 120ms) and built durable AWS multi-region telemetry workflows with idempotency, retries, and monitoring.

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Antara Bhavsar - Mid-level Software Engineer specializing in cloud-native systems and Android development in Bloomington, IN

Mid-level Software Engineer specializing in cloud-native systems and Android development

Bloomington, IN3y exp
Indiana UniversityIndiana University Bloomington

Application-focused software engineer with experience at Amazon and Motorola shipping production systems ranging from developer monitoring/on-call tooling (Alcazar, ~40% MTTR improvement) to consumer AI features used by 100K+ users. Currently building an AI/ML-driven platform with a Python/FastAPI backend on AWS (ECS/RDS/S3) and has handled real production latency/scaling incidents end-to-end.

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Prajit Mohan - Junior QA Engineer specializing in test automation for web applications in Oakland, CA

Prajit Mohan

Screened

Junior QA Engineer specializing in test automation for web applications

Oakland, CA3y exp
CognizantUC Berkeley

QA automation engineer with healthcare web experience who owned an end-to-end automated test suite (Java/Cucumber/Selenium and Cypress) and integrated it into CI/CD (Jenkins to GitHub Actions, qTest DoD gates). Known for boosting regression coverage to ~93%, stabilizing flaky Cypress tests, and catching production-impacting pipeline/environment redirect issues through workflow updates and cross-browser/regional scenario testing.

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Deepika Gotla - Senior Technical Support Engineer specializing in Azure Cloud & Generative AI in Bellevue, WA

Deepika Gotla

Screened

Senior Technical Support Engineer specializing in Azure Cloud & Generative AI

Bellevue, WA7y exp
MicrosoftSUNY New Paltz

Microsoft cloud/infra engineer with 5+ years supporting enterprise Azure environments, specializing in security-focused networking (private endpoints, DNS) and production troubleshooting across Azure Front Door/App Gateway WAF/AKS. Has implemented posture improvements via Defender for Cloud, Azure Policy, and RBAC tightening, and also designs secure AWS agent/scanner integrations and modern EKS/GitHub Actions/Secrets Manager observability-enabled SDK rollouts.

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AC

Mid-level AI/ML Engineer specializing in NLP, Generative AI, and predictive analytics

New Jersey, USA5y exp
JPMorgan ChaseStevens Institute of Technology

GenAI/LLM engineer who architected and deployed a production RAG “research assistant” for JPMorgan Chase’s regulatory compliance team, focused on safety-critical behavior (mandatory citations, refusal when evidence is missing). Deep hands-on experience with LlamaIndex, Pinecone, Hugging Face embeddings, LangGraph agent workflows, and metric-driven evaluation (golden sets, TruLens), including a reported 28% relevancy lift via cross-encoder re-ranking.

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SS

Shawn Souto

Screened

Director-level Engineering Leader specializing in AI and enterprise SaaS

Newport Beach, CA17y exp
SAPDeVry University

Engineering leader who has operated effectively in both a VC-backed startup and SAP, combining director-level org leadership with day-to-day technical depth. Notable for re-architecting integrations that produced a 3x revenue gain, leading a 90-engineer matrixed organization, and staying hands-on in GenAI, infrastructure, and full-stack problem solving.

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SR

Sanjana Reddy

Screened

Mid Backend Software Engineer specializing in cloud-native microservices

Remote, USA4y exp
MercuryArizona State University

Product-minded software engineer with experience shipping AI-powered financial insights (spend forecasting, cashflow, credit optimization) and building real-time analytics systems using React/TypeScript and FastAPI. Has designed microservices with RabbitMQ/gRPC and strong observability (Prometheus/Grafana/OpenTelemetry), and also built an internal Figma plugin adopted by designers that reduced export time by 50%.

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SD

Shimao Du

Screened

Junior Full-Stack Engineer specializing in cloud, AI, and distributed systems

Pittsburgh, PA2y exp
Snapbit LLCCarnegie Mellon University

Full-stack engineer from early-stage startups who has owned AI products end to end, from B2B document intelligence platforms on AWS to an HVAC voice assistant and a GCP-based RAG research system. Stands out for combining hands-on backend/infra depth with team leadership in lean environments, and for shipping scalable AI systems that contributed to roughly 1 million yuan in sponsorship.

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