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Vetted Troubleshooting Professionals
Pre-screened and vetted.
DevOps Engineering Manager specializing in Kubernetes platforms and Azure cloud infrastructure
Senior Cloud DevOps Engineer specializing in AWS/Azure automation and Kubernetes
Senior DevOps Engineer specializing in CI/CD, IaC, Kubernetes, and cloud security compliance
Mid-level Cloud Platform Engineer specializing in AWS and Kubernetes
Mid-level Quality Engineer specializing in medical device and pharmaceutical manufacturing
Senior Customer Success & Account Management leader specializing in B2B SaaS growth
Director-level Field Service & Operations Leader in Life Sciences Instrumentation
Director-level QA Supervisor specializing in mobile game testing and QA operations
Mid-level Game QA Tester specializing in multi-platform functionality and live ops testing
Senior QA/UAT Testing Professional specializing in enterprise test management and compliance
Senior Video Editor specializing in news and digital video distribution
Mid-level Hardware & Embedded Systems Engineer specializing in robotics and ML
Junior Technical Solutions Engineer specializing in Epic EMR and healthcare IT
Senior Technical Support Engineer specializing in SIEM and security detections
Senior Site Reliability/DevOps Engineer specializing in AWS/Azure Kubernetes and CI/CD
Senior Customer Success Manager specializing in Technical B2B SaaS
Jed Tabrilla
Junior Sales & Marketing Analyst specializing in Meta ads and e-commerce growth
“Growth marketer focused on the creator/UGC ecosystem (TikTok/Instagram), sourcing and scaling performance-based creator partnerships for DTC/e-commerce brands. Uses rigorous attribution and funnel-stage creative testing to optimize paid social, including a GTM initiative that cut CPA by 25% while maintaining contribution margins.”
Joseph Farghal
Intern Full-Stack Software Engineer specializing in automation and data-driven systems
“Early-career engineer with Charles Schwab internship experience building and testing production-bound internal APIs, emphasizing architectural fit, stakeholder alignment, and systematic debugging. Also has academic Python/ML experience analyzing Oura Ring biometric data and exposure to multi-agent robotics through coursework and RoboSub.”
vineetha Pulipati
Mid-level Software Engineer specializing in backend microservices and cloud data pipelines
“Backend engineer with Morgan Stanley experience building and owning an end-to-end Python FastAPI microservice for high-volume market data used by trading and risk systems. Strong in performance tuning and reliability (PySpark, Redis caching, async APIs), real-time streaming with Kafka, and production operations (Docker/Kubernetes, GitOps-style CI/CD, monitoring). Has led cloud/on-prem migration work across AWS and Azure, including fixing Azure Synapse performance issues via query and pipeline redesign.”
Akshay Khan
Mid-level Backend Software Developer specializing in cloud-native microservices
“Backend engineer with American Express experience maintaining an internal Python/Flask rewards simulation microservice used by product analysts and QA. Demonstrated strong performance and scalability work: moved batch simulations to Celery, added Redis caching to cut DynamoDB latency, and tuned Postgres/SQLAlchemy queries with EXPLAIN ANALYZE and composite indexes (bringing API responses under ~200ms by queueing jobs). Also has experience integrating ML via Flask-based model-serving APIs (scikit-learn/LightGBM packaged with joblib) and designing multi-tenant data isolation and tenant-specific configuration systems.”
Yurong Luo
Senior Data Scientist/ML Engineer specializing in scalable ML and LLM systems
“Built and deployed an end-to-end product that brings a research-paper approach into production for large-scale time-series clustering, with attention to partitioning, latency, and scalability. Also designed a Python-based backend validation service (comparing outputs to database ground truths) and handled production reliability issues by reproducing dataset-specific crashes and hardening corner-case behavior with client-friendly errors.”