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Vetted Blue-Green Deployment Professionals
Pre-screened and vetted.
Senior Software Engineer specializing in cloud-native healthcare platforms
Staff Full-Stack Engineer specializing in data engineering and real-time event platforms
Staff Full-Stack & Platform Engineer specializing in cloud-native distributed systems
Senior AI/ML Engineer specializing in GenAI, agentic systems, and healthcare AI
Staff Software Engineer specializing in Healthcare SaaS and real-time systems
Mazhar Haq
Senior AWS Cloud Architect and Technical Leader specializing in security, migrations, and cost governance
“Infrastructure/platform engineer with strong AWS and hybrid on-prem networking depth, spanning Kubernetes platform engineering (IaC, autoscaling, GitOps, observability) and large-scale VMware operations. Managed thousands of VMs across 56 US military bases/airports and has resolved real production hybrid incidents involving BGP/Direct Connect route advertisement and prefix-limit constraints.”
Nikhil Reddy
Mid-level AI/ML Engineer specializing in GPU inference and LLM platforms
“Built and deployed an LLM-powered platform that turns models into scalable REST/gRPC APIs, focusing on keeping GPU-backed inference fast and stable during traffic spikes. Experienced with AWS orchestration (EKS/ECS/Step Functions), safe model rollouts, and production-grade monitoring/testing for reliable AI agents and workflows.”
Shaji Nair
Principal Cloud & Digital Transformation Architect specializing in Financial Services and Data Platforms
“Technology-first venture builder with strong familiarity in the VC/accelerator landscape, specializing in greenfield innovation, M&A, and large-scale transformation/modernization. Described building a venture-funded retail banking greenfield startup to integrate lending-as-a-service for SME lending while meeting federal and local financial services compliance requirements.”
Mid-level Full-Stack Java Engineer specializing in scalable microservices and real-time data systems
Senior Full-Stack Engineer specializing in cloud-native .NET microservices
Senior AI/ML Engineer specializing in personalization, recommendations, and forecasting
Mid-level Full-Stack Engineer specializing in AI platforms and FinTech
Senior Backend Engineer specializing in Healthcare & Cloud Platforms
Mid-Level Full-Stack Software Engineer specializing in cloud-native systems and FinTech
Mid-level Software Engineer specializing in backend systems, billing, and real-time data pipelines
Senior Azure DevOps Engineer specializing in cloud architecture, IaC, and DevSecOps
Ali Rezafard
Director of Engineering specializing in cybersecurity SaaS platforms and cloud-scale backend systems
“Director of Engineering at Proofpoint for 8 years, leading architecture and integration of Java microservices within a detection platform. Demonstrates pragmatic delivery leadership—incurring short-term cost to meet launch deadlines, then systematically paying down technical debt and optimizing AWS spend—plus a disciplined, long-horizon approach to backward-compatible API/schema evolution across many dependent services.”
Kaushik Sriram
Mid-level Software Engineer specializing in event-driven FinTech backend systems
“Senior/Staff-level backend/platform engineer who owned Stripe’s global payout settlement system end-to-end, building an event-driven Python/Kafka platform processing millions of events daily across 30+ countries. Deep experience operating high-reliability distributed systems in production (incidents, replays/backfills, schema evolution, observability) and scaling on AWS/EKS with strong testing and deployment practices.”
Chandra sai kiran Kammari
Mid-level Machine Learning Engineer specializing in fraud detection and real-time personalization
“ML/LLM engineer with Stripe and Adobe experience who productionized a transformer-based Payments Foundation Model for real-time fraud detection at global scale (billions of transactions). Built petabyte-scale ETL/feature pipelines (Spark/EMR, Airflow, dbt, Kafka/Flink) and achieved <100ms multi-region inference (EKS, TorchServe, edge/Lambda, GPU/CPU routing) with strong PCI-DSS/GDPR compliance and explainability (SHAP/LIME), reporting a 64% fraud accuracy improvement.”