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Vetted Azure DevOps Professionals
Pre-screened and vetted.
Emma Clausen
Senior Full-Stack Engineer specializing in web platforms and mobile apps
“Backend/platform engineer with experience at Microsoft, Uber, and Gusto building production AI-agent automation systems in Python (AutoGen) and cloud-native microservices on Kubernetes across AWS/Azure. Has delivered zero-downtime migrations and high-throughput real-time streaming pipelines (Kafka/WebSockets/Redis), and is strong in GitOps/ArgoCD-driven CI/CD with reliable rollouts and rapid rollback.”
Abhishek Soppanna
Mid-level DevOps Engineer specializing in cloud-native infrastructure on AWS and Azure
“DevOps/SRE focused on cloud-based distributed systems, with strong hands-on Kubernetes production experience (microservices deployments, Helm, probes, resource tuning, CI/CD and Docker build standardization). Demonstrated end-to-end troubleshooting across application, infrastructure, and networking layers—e.g., isolating degraded storage via node disk I/O metrics and restoring performance by draining the node and replacing the volume. Builds Python automation for operational reliability, including scheduled Kubernetes secrets rotation integrated with an external secret manager.”
Senior Software Engineer specializing in cloud-native SaaS and event-driven microservices
Senior Software Engineer specializing in full-stack web platforms and cloud-native backend systems
Mid-level AI/ML Engineer specializing in GPU-accelerated LLMs, RAG, and production MLOps
Executive Engineering Leader (VP/CTO) specializing in cloud-native platforms and AI/ML
Mid-level AI/ML Engineer specializing in LLMs, search ranking, and multimodal ML
Senior DevSecOps Engineer specializing in secure cloud-native CI/CD platforms
Senior Full-Stack Software Engineer specializing in cloud and enterprise web platforms
Mid-Level Software Engineer specializing in backend, cloud, and CI/CD automation
Mid-level Machine Learning Engineer specializing in LLMs, ranking, and scalable ML systems
Senior Full-Stack Engineer specializing in scalable cloud platforms and AI integrations
Senior Full-Stack Engineer specializing in AI/GenAI and cloud-native platforms
Senior Software Engineer specializing in cloud platforms for healthcare and e-commerce
Senior Software Engineer specializing in cloud platforms, data pipelines, and ML
Intern Machine Learning Engineer specializing in LLM systems and recommendation/search
Senior Software Engineer specializing in AI/ML, search, and scalable cloud platforms
Staff-level Software Engineer specializing in .NET microservices for FinTech and Healthcare
Brian Sanders
Senior Backend Engineer specializing in GenAI, LLMs, and scalable data pipelines
“Backend/ML platform engineer from Snapsheet who owned production Python services and data pipelines for insurance claims, including an AI document classification/summarization FastAPI service on ECS/Fargate processing 1M+ documents/year. Strong in AWS infrastructure (Terraform, CI/CD, secrets/IAM, autoscaling), Glue/PySpark ETL with schema evolution controls, and legacy SAS-to-microservices modernization with safe, feature-flagged rollouts and measurable performance wins.”
Christopher Kanten
Senior Backend Engineer specializing in Node.js, Java, and regulated SaaS platforms
“Built a production LLM-powered root cause analysis agent for supply chain alerts that helped operations managers avoid manual dashboard investigation. Demonstrates unusually strong depth in agent reliability, orchestration, and observability, with concrete production practices like hallucination blocking, shadow testing on 500 cases, and data-driven improvements that raised user agreement to 94% while cutting GPT-4 usage by 60%.”
Harish Kasu
Mid-level AI/ML Engineer specializing in Generative AI, RAG, and MLOps
“AI/LLM engineer with production experience at NVIDIA and Microsoft, including building a RAG-based enterprise knowledge assistant that improved accuracy by 42% and scaled to thousands of queries. Deep in inference optimization (TensorRT-LLM, Triton, quantization, speculative decoding) and MLOps/observability (Prometheus/Grafana, MLflow, LangSmith), plus orchestration with Kubeflow/Airflow across multi-cloud.”