Vetted Azure DevOps Professionals

“QA automation engineer focused on end-to-end quality for a CMS lien registration workflow, owning a Playwright-based regression suite covering high-risk paths (creation, amendments, cancellation, batch file validation). Demonstrated impact by catching a UI change that bypassed required-field validation pre-release, stabilizing flaky CI tests using network-response signals, and driving clearer acceptance criteria and observability improvements (request IDs in logs) through cross-functional collaboration.”

“IBM Power/AIX infrastructure engineer who has owned a sizable production estate (50 Power servers / ~200 LPARs) spanning VIOS/HMC, SAN/NFS, and PowerHA clusters. Demonstrates strong incident leadership (LPAR outage + split-brain recovery) and a process-improvement mindset with measurable reductions in recurrence/MTTR, while also bringing modern DevOps/IaC experience (Jenkins, ArgoCD, Terraform, security scanning, canary/blue-green).”

“Software QA professional (non-gaming) with strong end-to-end release and production support experience in Agile environments. Led a large QA effort migrating customers from a legacy application to a new platform, owning test scope, deployment coordination, release sign-off, and issue troubleshooting. Known for evidence-rich bug reports (API-driven repro, logs/devtools) and disciplined tooling/documentation across Azure DevOps, Jira/Rally, and Confluence.”

“UE5 UI/tools-focused developer who emphasizes production-ready, designer-friendly workflows: built a C++ enemy-spawn timeline actor with Slate-driven editor customization and memory-efficient event storage. Implemented an Enhanced Input keybinds menu (two keys per action) using MVVM-style separation and event dispatchers for low coupling and testability, and uses Unreal Insights to drive performance fixes (including refactoring tick-heavy plugin work and batching data queries to prevent UI hitches).”

“Software engineer with JPMorgan Chase experience delivering end-to-end fintech features (Next.js/React/Node/Postgres on AWS) and measurable performance gains. Built and productionized an AI-native credit decisioning workflow combining LLMs, vector retrieval, and a rules engine with strong governance (bias checks, auditability, human-in-loop), improving precision and cutting underwriting turnaround time by 40%.”

“Backend/ML engineer who built a job-search automation SaaS using a modular Selenium ETL pipeline, rigorous testing/observability, and a cost-optimized two-pass LLM ranking approach. Has led high-integrity data extraction from messy multi-city PDF records (95% integrity) and managed modular production rollouts for a 20+ engineer team, with a strong security focus (deny-by-default, row-level access control) in an AI-assisted grading platform.”

“Backend/data engineer focused on production Python and AWS: built FastAPI REST services and a containerized ECS Fargate + Lambda architecture deployed via Terraform/CI-CD. Strong in data engineering (Glue/S3/Parquet/RDS) and operational reliability (CloudWatch/SNS, retries, schema-evolution handling), with experience modernizing legacy SAS reporting into Python microservices using feature flags and parity validation.”

“Full-stack engineer with experience building customer-facing fintech mobile features end-to-end (loan estimate comparison) and scaling event-driven microservices in enterprise environments (Verizon). Has designed TypeScript/React/Node systems with queues/caching and built an internal rule-engine for bulk Excel ingestion that reduced data errors and manual rework through automated validation.”

“Backend engineer who owned an order management API built with Python/FastAPI and PostgreSQL, integrating payment and shipping providers with strong reliability patterns (idempotency, async workers, retries/backoff, circuit breakers). Experienced deploying services to Kubernetes using a GitOps model with ArgoCD (auto-sync, self-healing, pruning, rollbacks) and building high-volume Kafka streaming pipelines. Has also supported phased cloud-to-on-prem migrations with a focus on security monitoring/SIEM log continuity.”

“Product-focused full-stack engineer (Spring Boot/Django + React/TypeScript) with deep experience building multi-tenant, enterprise workflow and supply-chain/order-tracking systems. Owned an end-to-end Workflow SLA Breach Prediction & Alerting feature integrating Azure ML for a cloud workflow platform used by ~10,000 enterprise users, and has hands-on AWS operations experience resolving real production latency/scaling incidents via query optimization and Redis caching.”

“JavaScript/React engineer with hands-on open-source library contribution experience, including thoughtful PRs that improved error handling, API flexibility, and added features backed by tests and documentation. Demonstrates a profiling-first approach to UI/runtime performance (memoization, component splitting, render-path optimization) and strong community support skills—reproducing edge cases, delivering sustainable fixes, and communicating workarounds and releases.”

“Backend-leaning full-stack engineer who led a legacy monolith-to-microservices migration (OAuth, Redis, ActiveMQ) while shipping incrementally via CI/CD to avoid user disruption. Strong in search/filter experiences and performance tuning (Solr schema + relevance boosting) with measurable impact (login reduced to ~5s), plus React/TypeScript UI work including configuration-driven filters and shareable URL state.”

“QA automation engineer with deep experience owning end-to-end Cypress/JavaScript test suites (smoke, regression, and API contract tests) integrated into GitHub CI with merge gating and rich reporting. Demonstrated healthcare enrollment domain expertise by catching a critical eligibility versioning/overwrite defect via API + DB assertions that UI tests missed, then hardening the pipeline with contract tests and idempotency checks.”

“QA automation engineer from Bajaj Finance who owned end-to-end automated test suites for large-scale web/mobile products (70M+ users), building Python and API automation integrated with Jenkins/Azure DevOps. Drove measurable quality outcomes (40% less regression effort, 35% fewer production defects, 98% successful UAT across 25+ releases) and has strong fintech lending domain experience (loan disbursement/repayment/eligibility).”

“Senior full-stack engineer with strong healthcare domain experience who has shipped an Azure OpenAI RAG-based patient medication support chatbot to production, driving ~10K queries/month and a reported 38% reduction in call center volume. Also builds polished real-time React/TypeScript pharmacy tooling and operates large-scale Python/Spark ETL pipelines (~12M records/day) with strong API design, observability, and cloud deployment experience across Azure/Kubernetes and AWS.”

“Built and deployed a production LLM/RAG clinical document understanding and summarization system for healthcare, focused on reducing manual review time while meeting strict accuracy, latency, and compliance needs. Demonstrates strong MLOps/orchestration depth (Airflow, Kubernetes, Azure ML Pipelines) and a rigorous approach to hallucination mitigation through layered, source-grounded safeguards and stakeholder-driven requirements with physicians/compliance teams.”

“Frontend engineer who led Bentley’s flagship design system from a greenfield codebase to adoption across every major Bentley product, emphasizing maintainability and high UX polish. Built complex React+TypeScript interfaces like a Figma/Photoshop-style layers tree, applying advanced performance techniques (skeleton-first loading, transitions, memoization, deferred rendering) and iterative feature-flagged rollouts driven by user feedback.”

“Hands-on engineer focused on productionizing LLM-powered assistants: builds RAG pipelines with guardrails, response schemas, and citation-grounded outputs, then hardens them with explicit NFRs (latency, uptime, security, cost). Experienced diagnosing agentic/LLM workflow issues in real time using observability and stepwise isolation, and supports go-to-market via developer demos, workshops, and pre-sales technical evaluations in microservices/Spring Boot environments.”

“Software engineer and University of Chicago graduate teaching assistant who built a full-stack internal analytics dashboard (React/TypeScript + Node/Express) and worked in RabbitMQ-based microservices with Prometheus/Grafana observability. Also created an AI-powered ERD diagram generator (React + MermaidJS + OpenAI) adopted by students to save hours on database assignments, using validation loops to ensure valid Mermaid output.”

“Backend-focused Python engineer who builds modular Flask services on AWS and specializes in performance/scalability work across data-heavy APIs. Has concrete wins in query optimization (1.5s to <200ms) and high-throughput async processing (Celery+Redis, ~40% throughput gain), plus experience serving scikit-learn text classification models via containerized REST services and designing multi-tenant data isolation strategies.”

“Python backend engineer who owned an end-to-end Django/DRF authentication and account-management module (JWT, RBAC, email verification) and optimized token validation performance. Has hands-on Kubernetes + Helm delivery with GitOps via ArgoCD (multi-environment app-of-apps, drift detection/rollback) and has supported a cloud-to-on-prem migration using staged testing and phased cutover. Also built and scaled a Kafka-based real-time user activity tracking pipeline with reliability and backpressure controls.”

“Backend/infrastructure-focused engineer building AI-agent products for small businesses, including a customer-service agent platform with intent routing, RAG over Pinecone, and external booking API integration. Has shipped Python/FastAPI services with JWT auth, versioned APIs, Docker deployments to AWS EC2 via GitHub Actions, and production monitoring with Prometheus/Grafana.”

“AAA sports game QA tester who supported full development through launch and live updates, owning gameplay stability/regression risk. Experienced in triage-driven prioritization and in diagnosing complex crash issues (including thread synchronization) using evidence-backed Jira reports, then hardening coverage with stress/concurrency/soak and CI-integrated regression suites.”

“Cloud/DevOps engineer operating across AWS and Azure, running Kubernetes workloads with secure CI/CD (GitHub Actions/Azure DevOps) and Terraform IaC. Has supported AIX/PowerHA systems in hybrid environments—handling failover testing, incident recovery, and performance troubleshooting (including multipath/storage-path issues)—and has led cutovers by managing dependencies, rollback, and stabilization.”