Vetted Microsoft Azure Professionals

“Backend/ML engineer who has built both enterprise data pipelines and real-time AI products: modular Python (Flask/FastAPI) services integrating automation scripts and low-latency ML inference (MediaPipe, PyTorch) plus OpenAI-powered feedback. Demonstrated measurable performance wins (~30% faster HR workflows; ~40% faster AWS pipelines across 100+ Oscar Health feeds) and strong multi-tenant/data-isolation patterns (schema-based isolation, RBAC, microservices).”

“Backend engineer who built an agentic LLM system for private equity/finance that answers questions over enterprise contracts and documents using a vector-db RAG pipeline. Differentiator is a trust-focused citation framework (with highlighted source text) to reduce hallucinations in high-stakes workflows, plus strong DevOps experience deploying microservices on Kubernetes with Helm/GitOps and building Kafka real-time pipelines.”

“Backend engineer (IpserLab) who owned Python services for a production quiz/analytics platform, focusing on reliability and low-latency behavior under peak load. Hands-on with Kubernetes + Docker deployments and GitHub Actions CI/CD in a GitOps-style workflow, including solving configuration drift and enabling fast rollbacks. Also implemented Kafka-based event streaming with idempotent consumers and strong observability (lag tracking, structured logging, alerting).”

“Cloud/SRE-style engineer at TDS supporting revenue-critical transportation SaaS platforms on AWS/GCP with Kubernetes. Has hands-on experience leading high-impact production work including DDoS mitigation, zero-downtime MSSQL→PostgreSQL migration using CDC, and building secure GitHub Actions + ArgoCD delivery pipelines and Terraform-based GKE infrastructure.”

“CTO/Chief Architect who rebuilt an IoT platform from a fragile legacy stack into an AWS-based, multi-tenant cloud-native system supporting 50k+ connected devices and 10M+ monthly events, then layered in real-time data pipelines and ML anomaly detection. Known for tightly aligning roadmaps and OKRs to business KPIs (onboarding speed, uptime, velocity) and for scaling teams into domain-focused pods; previously led a shift from LAMP to event-driven Node.js microservices using MQTT and message queues.”

“ML engineer with hands-on experience taking a Gaussian Process Regression-based intelligent survey timing system from build to real-world deployment, including a 3-week RCT on 120 participants and measurable improvements (15% response rate, 23% data quality). Also served as a key technical resource at CData for customer-facing demos and debugging hundreds of production issues, bridging engineering with Sales and Customer Success.”

“Startup-focused engineering leader applying for a CTO role; previously served as founding CTO of a tech startup and held engineering/architecture roles across several others. Evaluates new ventures through market research and market demand, and emphasizes building from the ground up with strong teams (has not personally participated in fundraising).”

“Cloud/Linux infrastructure engineer focused on high-availability AWS platforms (EKS/EC2) with strong observability and incident response ownership. Has hands-on experience building secure CI/CD (GitHub Actions/Jenkins) and Terraform-based IaC at scale, including resolving real production issues like peak-traffic latency and Terraform remote state locking; transparent about not having direct IBM Power/AIX/PowerHA production ownership.”

“DevSecOps/AWS infrastructure engineer at Madison Logic who owns a 15-account AWS footprint and treats nearly all AWS resources as code (Terraform/CloudFormation). Led a CI/CD platform migration (Bitbucket → GitLab + GitHub Actions) supporting WordPress and containerized microservices, improving release frequency to weekly/daily, and has hands-on production incident response experience on ECS Fargate using Datadog with fast rollback via immutable ECR tags and task definition revisions.”

“Works on clinical trial applications and data pipelines, including AWS Lambda-based file transfer workflows for clinical study metadata. Has hands-on experience hardening production systems by adding observability, SSH/auth exception handling (Paramiko), retries/timeouts, and validating changes across SIT/UAT/prod. Also supports adoption through tailored technical demos for new teams and vendor partners integrating into their workflows.”

“Hands-on LLM/RAG engineer with production experience improving retrieval quality and stability by addressing messy data, vector DB inaccuracy, and top-K issues—ultimately redesigning to hybrid search with tuned keyword/semantic weighting and MCP-based data supplementation. Also brings strong AKS/Kubernetes deployment experience, optimizing CI/CD speed via lightweight local Docker validation and decomposing pods to avoid full rebuilds, plus a metrics-driven approach to agent/workflow testing and traceability.”

“Backend engineer who built and scaled a zero-to-one social product backend using Supabase (Postgres, Edge Functions, Auth, Realtime) plus Neo4j for graph-based friend recommendations. Demonstrates strong production rigor: staged rollouts with metrics, incident rollback/postmortems, and complex schema refactors using expand-contract/dual-write with reconciliation and feature flags. Notably proactive about edge cases like geo-boundary realtime delivery and idempotent retry safety.”

“Backend/data engineer with production experience across event-driven Python ingestion services on AWS (EventBridge/SQS/MongoDB), serverless APIs (Lambda/API Gateway), and analytics ETL (Glue → Redshift). Has modernized legacy reporting into Node.js/React systems and demonstrated measurable SQL performance wins (minutes to seconds) plus strong incident ownership with validation, DLQs, and alerting.”

“AI Engineer with production experience building an LLM-powered conversational scheduling assistant (rules-based + OpenAI GPT agents) and improving responsiveness by ~40% through architecture optimization. Strong in orchestration (Airflow), containerized deployments, and data quality (Great Expectations/PySpark), with prior work automating population health reporting pipelines (Azure Data Factory → Snowflake) and delivering insights via Tableau to non-technical stakeholders.”

“Software developer with EdPlus experience building pragmatic internal tools (Next.js/TypeScript) and cloud automations (AWS) that feed Google Sheets and Looker Studio dashboards for operational visibility across 30+ student workers. Also worked on an IEEE Xplore-published missing-person tracker using a SPARQL graph database on Azure with a TypeScript/React frontend, and has experience navigating legacy access constraints (OpenVPN) while enabling remote VR previews via ngrok.”

“Frontend-focused engineer who has delivered an end-to-end React SPA with a .NET 9 backend on Azure, deploying via Azure Container Apps and leveraging zero-downtime deployment slots. Built complex TypeScript UI flows (10-page form with global/partial save and custom validation) using Redux + MUI integrated from Figma, and emphasizes quality with RTL/Vitest plus Selenium automation (~95% coverage) and analytics-driven iteration (Heap, Alida, GTM).”

“Product-minded software engineer who owned a Shopify POS app end-to-end at Swym, shipping an MVP and then scaling iteration speed with E2E automation and CI/CD—resulting in a Shopify Badge, Top-5 App Store ranking, and +40% new user acquisition. Also built an ESG insights tool using React/TypeScript + FastAPI with Snowflake and a RAG pipeline, plus microservices patterns (async jobs, queues, DLQs, autoscaling) and internal Metabase/SQL analytics dashboards.”

“Built and deployed a production AI document Q&A (RAG) platform that lets non-technical users query hundreds of PDFs/Word files, cutting search time from hours to seconds. Experienced with scaling retrieval pipelines (chunking, embeddings, vector search, batching/caching) and orchestrating reliable workflows using AWS Step Functions/Airflow with robust retries, monitoring, and fallbacks.”

“JavaScript engineer who effectively "maintains" an internal open-source-style React/Node.js shared library used by multiple teams—owning API stability, semantic versioning, CI/testing, logging, and documentation. Demonstrates strong cross-team debugging and change-management skills (schema-driven refactors, feature flags, validation layers) to ship new features without breaking existing workflows, plus a profiling/benchmarking-driven approach to performance.”

“Backend engineer at Esurgi focused on real-time clinical workflow systems, improving API reliability, performance, and security. Has hands-on experience with FastAPI/Pydantic, JWT/RBAC and row-level data isolation, plus Kafka-based real-time processing—including fixing duplicate-processing edge cases via idempotency and offset management and rolling out refactors safely with feature flags and staged deployments.”

“Silicon Valley operator with ~30 years of experience as a board member, advisor, VC, founder, and turnaround executive, claiming 50+ venture-backed turnarounds. Has driven outsized outcomes including a $1B Nokia spinout and a 9-figure Jaspersoft exit to TIBCO, and is known for pragmatic, people-and-financials-first operational diagnosis (including CRM forensics) and rapid team scaling via structured hiring pipelines.”

“LLM/AI practitioner focused on productionizing LLM assistants for customers, with emphasis on reliability, security, and data privacy (RAG architecture, guardrails, RBAC, data masking, monitoring and automated evals). Experienced in hands-on developer workshops and in partnering with sales to run tailored demos/pilots that drive broad customer adoption.”