Vetted Microsoft Azure Professionals

“NYC-based startup founder/CTO who sold products to Omnicom and Sprinklr, then built an AI-powered cultural insights engine inside Omnicom using AWS Lambda + ML to process ~1M items/day and reached ~$1MM ARR in year one. Former senior leader at Sprinklr managing 200+ people globally, delivering enterprise martech solutions with SLAs and high-reliability social data pipelines (Twitter firehose).”

“Enterprise cloud/SaaS customer success leader who owned a strategic $102M Azure commitment end-to-end, rescuing a Kubernetes migration by formalizing Sev A/B triage/escalation ownership and executive governance. Drove measurable outcomes including restored executive confidence and consumption growth from $1M to $2M/month (~30% adoption growth) by tying stabilization milestones to migration velocity, forecasting, and expansion strategy.”

“McKinsey practitioner who built and deployed production LLM systems for consultants/clients, including a Power BI-integrated multi-agent chatbot (RAG + text-to-SQL + formatting) with custom Python orchestration, verification loops, and a 100+ case eval set achieving ~95% consistency. Also delivered a taxonomy-mapper agent that standardized inconsistent labeling for C-suite stakeholders, cutting a process from >2 weeks to <30 minutes through demos and business-focused communication.”

“CRO/operator with experience at both AWS and a rapidly scaling Hawaii-based startup (Mana'olana International), focused on building lightweight but scalable operating systems. Known for implementing QBR/OKR rhythms, capacity/territory planning, KPI dashboards, and ROI-tied funding controls, and for mentoring founders through GTM accelerator work (Blue Startups) using a minimum-viable-process approach.”

“Backend engineer who helped redesign and refactor Forma’s backend during an app rewrite, emphasizing modularity, maintainability, and A/B testing support while delivering feature parity on a quarter-long timeline. Led a careful database migration using parallel databases with schema differences, validating integrity via staging and SQL checks, and has experience debugging subtle computer-vision overflow edge cases.”

“Built and shipped an LLM-powered data quality assistant that generates maintainable validation checks from metadata while executing validations via Great Expectations, exposed through FastAPI and integrated into Airflow-managed pipelines. Emphasizes production reliability (structured outputs, guardrails, monitoring, versioning, human review) and works closely with compliance/operations teams to deliver clear, auditable, user-friendly AI outputs.”

“Operations/engineering leader from Poly who optimized a professional headset portfolio by aggressively prioritizing technical debt and consolidating HW/SW platforms (down to 2 each), accelerating time-to-market by ~6 months and enabling 3–6 month variant cycles. Also drove AI-enabled quality improvements by leveraging JIRA bug data to automate test case creation and expand coverage, while aligning engineering and product management around MVO delivery.”

“Platform/backend engineer focused on Kubernetes at scale: built a Java control-plane service for multi-region cluster provisioning/monitoring/upgrades using Kafka-driven async workers, and solved peak-load provisioning failures by eliminating blocking I/O and dynamically scaling consumers. Also shipped an LLM-assisted Kubernetes troubleshooting/remediation feature that pulls Prometheus logs/metrics into prompts and uses guardrails (confidence thresholds + human-in-the-loop) to prevent risky actions.”

“Engineering leader who modernized and unified a fragmented product suite at Milestone via a multi-year cloud-native roadmap, delivering an MVP in three quarters and boosting team velocity by 40% through cross-functional squads. At Prometheum, led a trust-building hybrid architecture (AWS control plane + customer-hosted data plane) using Kubernetes to ensure sensitive enterprise data never left customer networks while remaining cloud-agnostic across providers.”

“Backend/data engineer from Oscar Health specializing in healthcare claims systems on AWS. Built HIPAA-compliant real-time services (FastAPI/Postgres/Kafka on EKS) and serverless ingestion pipelines, and led modernization of a legacy SAS claims pricing system to Python/Spark with rigorous parity validation. Demonstrated measurable impact with high uptime/low latency services and major Snowflake performance and cost reductions.”

“Backend/data engineer with hands-on production experience across GCP (FastAPI microservices on Kubernetes) and AWS (Lambda, ECS Fargate, Glue). Has modernized legacy SAS batch systems into Python services with parallel-run parity validation, and has strong operational rigor in ETL reliability/monitoring plus proven SQL tuning impact (25s to <300ms, ~60% CPU reduction).”

“Built and shipped a production LLM-powered medical scribe that generates structured clinical visit summaries using RAG, strict JSON schemas, and post-generation validation to reduce hallucinations. Experienced in making LLM workflows deterministic and observable (structured logging/metrics/tracing) and in evaluation-driven iteration with metrics like schema pass rate and edit rate; collaborated closely with clinicians and policy stakeholders at Scale AI to drive adoption.”