Vetted Azure DevOps Professionals

Dinesh Guguloth

Screened

Mid-level Software Engineer specializing in full-stack cloud-native applications

New York, NY4y exp

“Full-stack engineer with cloud and GenAI experience who has owned production features end-to-end, including a reporting dashboard optimized from 14s to 5s using query/API refactoring and monitored via AWS CloudWatch. Also productionized an OpenAI-powered chatbot using LangChain with prompt design, guardrails, and evaluation via production logs and user feedback, and has led incremental legacy-to-microservices modernization with parallel run to avoid regressions.”

“Senior/Lead Frontend/Full-Stack engineer in Toronto with proven experience shipping high-stakes, real-time and regulated products across healthcare, legal/compliance, and fintech. Built a real-time compliance dashboard that survived a 400% data spike and a no-code workflow builder supporting 500+ nodes, with strong emphasis on performance engineering, type-safe architecture, and automated quality/rollout practices.”

“Built and owned UPS tracking/reporting and operations workflow dashboards, delivering customer-facing APIs and real-time React/TypeScript UIs backed by .NET Core. Experienced in high-volume microservices using IBM MQ/Azure Service Bus with strong reliability patterns (idempotency, retries, DLQ) and Azure-based observability, plus performance tuning across frontend and SQL-backed services.”

“Software engineer with hands-on experience building and maintaining a React accessibility utility/component library (open-source-style) used across university portals, emphasizing WCAG 2.2 compliance, robust focus/keyboard behavior, and Jest/React Testing Library coverage. Also built and maintained .NET Core microservices at the Florida Department of Transportation, including integrating AI-driven features, with strong ownership around observability, incident response, and performance-focused refactoring.”

“Backend/data engineer who builds Python (FastAPI) data-processing API services for internal analytics/reporting, emphasizing modular architecture, async performance tuning, and reliability patterns (health checks, retries, observability). Also migrated legacy on-prem ETL pipelines to Azure using ADF/Data Lake/Functions and implemented a near-real-time ingestion flow with Event Hubs plus watermarking to handle late events and deduplication.”

“Full-stack engineer with strong React/TypeScript and Java Spring Boot microservices experience who has built end-to-end task management and real-time, data-intensive dashboards. Demonstrates practical depth in security (JWT, RBAC, token refresh), performance optimization (indexing/aggregations, virtualization, caching), and cloud deployment (AWS, Docker, Jenkins, Kubernetes).”

“AI engineer with production experience building a LangGraph-based, stateful multi-agent system at MetLife to automate complex insurance claims adjudication, integrating document discovery, Azure Document Intelligence OCR/extraction, and health data analysis. Strong in agent orchestration and production deployment (Docker + FastAPI REST APIs), with a structured approach to reliability, evaluation, and stakeholder-driven requirements.”

“Backend engineer with cloud-native Python/Flask experience building high-throughput financial platforms (loan origination intelligent document processing and real-time fraud detection). Has scaled microservices on AKS with event-driven Azure messaging, delivered measurable performance gains (e.g., 700ms→180ms query latency; ~40% API improvements), and implemented strong security controls (OAuth2/JWT, Azure AD RBAC, audit logging, AES-256/TLS) for sensitive regulated data.”

“IBM Power/AIX infrastructure engineer with hands-on production experience across Power8/Power9 frames, VIOS and HMC, including resolving a production LPAR outage caused by vFC mapping issues. Has operated PowerHA clusters for critical finance workloads, running quarterly failover tests and handling an unplanned failover triggered by a network adapter failure, then improving resilience with redundancy and monitoring automation.”

“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).”

Filmon Tesfay

Screened

Senior Full-Stack Developer specializing in cloud-native FinTech and AI platforms

New York, NY8y exp

“Full-stack engineer with strong production ownership: built and operated a real-time transaction monitoring/fraud-alerting system using Java Spring Boot, Kafka, Docker, and AWS with CI/CD. Demonstrates metrics-driven operations (latency, stability, consumer lag, true/false positives) and reliability patterns for integrations (idempotency, retries/backoff, DLQs, reconciliation/backfills), plus modern React/TypeScript + Node/Postgres architecture experience.”

Mohith Venkata

Screened

Mid-level Full-Stack Developer specializing in cloud-native APIs and data workflows

Tukwila, WA4y exp

“Built and owned end-to-end ordering and inventory/order management systems for a wholesale distributor, delivering an MVP quickly and iterating based on direct observation of daily users. Experienced with TypeScript/React + Node.js layered architectures and microservices using RabbitMQ, including real-world scaling issues (duplicates, backpressure) and observability practices (correlation IDs, structured logging).”

Farida Poor

Screened

Junior Machine Learning Engineer specializing in NLP and multimodal transformers

Bay Area, CA3y exp

“Built and deployed LLM-powered agentic chatbot and text-to-SQL systems using LangGraph/LangChain (and Bedrock), structuring workflows as DAGs with planning/replanning and validation to improve tool-calling reliability and reduce hallucinations. Operates production feedback loops with online/offline metrics, drift detection, and LangSmith-based evaluation pipelines, and regularly partners with business stakeholders and clinicians using slide decks and visual charts.”

Ashutosh Meena

Screened

Junior Embedded Software Engineer specializing in IoT and microcontrollers

Chicago, IL2y exp

“Embedded/software engineer with hands-on Raspberry Pi work building a WhatsApp-controlled camera/servo system using TCP/IP plus Selenium automation of WhatsApp Web. Brings production DevOps experience from Infosys (Docker/Kubernetes, CI/CD, microservices, Kafka) and a methodical hardware/software debugging workflow using lab tools like oscilloscopes and multimeters.”

Rahul Solleti

Screened

Mid-Level Software Engineer specializing in cloud-native microservices and full-stack web apps

United States5y exp

“Backend/platform engineer focused on real-time financial fraud detection and transaction monitoring, building low-latency FastAPI + Kafka systems with strong reliability patterns (DLQs, idempotency) and cloud observability. Has hands-on Kubernetes delivery across AWS EKS and Azure AKS with automated CI/CD and GitOps-style deployments, plus experience migrating legacy C# / Java monoliths to containerized microservices using Terraform/ARM and zero-downtime rollout strategies.”

“Data analyst with cross-industry experience spanning insurance analytics at L&T Infotech and experimental imaging analytics at Mylyser. Stands out for building scalable SQL/PySpark data pipelines, standardizing business-critical metrics like claims lifecycle and policy retention, and delivering measurable impact such as 50%+ faster query performance and a 15% reduction in claims settlement time.”

“Backend-focused engineer with banking-domain deployment experience who has owned releases end-to-end, from discovery and API/database implementation through post-launch stabilization. Brings a reliability-first mindset across distributed systems, incident response, and messy real-world data handling, and has also applied that foundation to retrieval-based LLM workflows in production-oriented cloud environments.”

“Software engineer focused on backend and full-stack development who is already integrating AI deeply into day-to-day engineering workflows. Stands out for experimenting with multi-agent setups where separate agents handle planning, coding, review, testing, and documentation, while maintaining strong human oversight around quality, security, and performance.”

“Frontend engineer with hands-on experience building complex, real-time React/TypeScript products, including an AI-powered document Q&A dashboard and a geospatial analytics platform. Stands out for measurable performance wins—cutting UI interaction latency from roughly 300-800ms to 20-50ms—and for scaling map-based visualizations to tens of thousands of live entities using Mapbox GL, Deck.gl, WebGL, Web Workers, and Redux Toolkit.”

“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.”

“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.”