Vetted Microsoft Azure Professionals

Saswata Deb

Screened

Mid Backend Engineer specializing in AI systems and LLM infrastructure

India4y exp

“Early-to-growth-stage B2B SaaS engineer from Sentisum who combined Python backend, data pipeline, and applied AI work with direct customer-facing product input. Particularly compelling for startup roles: they owned systems end-to-end, migrated transcription infrastructure to cut costs by ~93%, and built scalable async export and data-processing workflows over large enterprise conversation datasets.”

“Backend/data engineer focused on AWS-based, low-latency event processing for market data and social-signal sentiment systems. Has led a monolith-to-event-driven migration with feature-flagged incremental rollout, and emphasizes production-grade security (OAuth2/JWT, secrets management, Supabase RLS) and data integrity (deduplication/idempotency) under high-volume spike conditions.”

“Backend Python engineer who has built an LLM agentic tutoring/assignment helper with a custom pipeline for parsing visually complex textbooks (integrating AlibabaResearch VGT and implementing missing preprocessing from the paper), improving RAG grounding with ~90% cleaner extracted text. Also led major platform scaling work by refactoring monolithic image processing into Celery-based async microservices on AWS (GPU/CUDA + S3), and implemented Kafka streaming for payment webhooks with strict ordering, idempotency, and multi-zone fault tolerance.”

“Software engineer with end-to-end ownership of a Qt/C++/QML desktop app for monitoring/configuring equipment, including hands-on UI performance optimization. Also built a web-based AI agent interface (React/TypeScript + Python Flask) with strong API contract discipline and async state handling, and improved microservices reliability using idempotency, DLQs, and observability. Created an internal CI/CD automation tool adopted across engineering and operations teams, adding safer rollbacks and better error messaging based on feedback.”

“Built SparkyAI, a gamified college-essay writing assistant (hackathon project at ASU in 2025) using React/styled-components, Firebase (OAuth/DB), and OpenAI APIs, with concrete scalability and performance measures like rate limiting, indexed queries, code splitting, and conversation caching. Also designed a global low-latency voice-to-LLM architecture leveraging WebRTC, regional containerized services, global load balancing, streaming STT/TTS, and end-to-end encryption with minimal logging.”

“Built a production lead-generation system using AI agents that researches the internet for relevant leads and integrates RAG-based contact enrichment/shortlisting aligned to existing CRM data, enabling sales reps to focus more on selling. Also has hands-on AWS data orchestration experience (Glue, Step Functions) moving raw data into Redshift and evaluates agent performance with human-in-the-loop plus BLEU/perplexity metrics.”

“Full-stack .NET/Azure engineer with end-to-end ownership of policy management microservices (React/TypeScript + C#/ASP.NET Core + Kubernetes) delivering significant performance and quality improvements (e.g., response time -35%, defects -30%, CSAT +18%). Also productionized an AI-assisted analyst workflow using Azure OpenAI with a RAG pipeline on Azure Cognitive Search, including rigorous prompt versioning, guardrails, and measurable impact (review time -40%, errors -55%). Led incremental legacy modernization via Strangler Fig and dual-write migrations with zero production regressions.”

“Cloud/infrastructure engineer with strong production operations background across AWS, Azure, and Kubernetes, supporting 30+ enterprise workloads for ~40,000 users. Demonstrated incident leadership (hybrid AKS-to-AWS routing outage) with a reported 60% MTTR reduction, plus hands-on CI/CD (Jenkins) and Terraform-based IaC for AWS (VPC/EC2/EKS). Lacks direct IBM Power/AIX/PowerHA experience but emphasizes transferable ops and troubleshooting skills.”

“Cloud-focused application security practitioner with hands-on AWS and Kubernetes experience, including securing a manufacturing monitoring platform (API auth, least-privilege IAM, CI/CD security checks) and troubleshooting a production data-ingestion outage caused by an overly restrictive IAM change. Experienced in implementing cloud-native security tooling (IAM Access Analyzer, Inspector, CloudWatch) and deploying monitoring/security agents via Kubernetes sidecars with Helm, Prometheus/Grafana, and Jenkins-driven CI/CD.”

“Data engineer who has owned production pipelines end-to-end—from Kafka/Airflow ingestion through SQL/Python validation and dbt transformations into Redshift/BI. Also built and operated a large-scale distributed web scraping platform (50–100 sites daily, ~5–10M records/day) with Kubernetes, Kafka queues, robust retries/DLQ, anti-bot measures, and backfill-safe raw HTML storage.”

Hammad Ur Rahman

Screened

Senior DevOps Engineer specializing in cloud infrastructure and CI/CD

Boston, Massachusetts11y exp

“IBM Power/AIX engineer who has owned a 150+ LPAR AIX 7.x estate with VIOS/HMC/vHMC and PowerHA in production, including real outage and failover recoveries. Also brings modern DevOps/IaC experience—built Jenkins pipelines deploying to AKS and implemented Terraform on AWS with remote state, locking, and drift management.”

Ali Zafar Zaidi

Screened

Senior Frontend/Full-Stack Developer specializing in React and Next.js

Hamilton, Canada8y exp

“Frontend engineer who has led architecture and delivery of large, data-driven React/TypeScript interfaces used by thousands of users, with strong emphasis on scalable structure, performance, and automated quality gates (CI/CD, Jest/Cypress). Recently building a resume screening application for McMaster University students and has experience shipping role-based (RBAC) features with tight cross-functional collaboration and PR-based QA deployments.”

Darion Jefferson

Screened

Mid-level IT & Cloud Security Specialist specializing in GRC, SOC workflows, and agentic AI automation

Petersburg, VA4y exp

“Builder/creator who ships practical AI automations and content workflows: created a no-backend website that uses ChatGPT to generate AI agents/manual workflows, and built an inbound/outbound receptionist using n8n and Retell AI (later migrated to Retell workflows). Also produces an AI-written/produced podcast with 55+ hosts and uses tools like Descript and Sora with make.com for batch content creation and scheduling.”

Satish Kumar Reddy

Screened

Mid-level AI/ML Engineer specializing in NLP, computer vision, and MLOps

Remote, NJ5y exp

“Built and deployed a production LLM/RAG intelligent document understanding platform for healthcare clinical documents (notes, discharge summaries, diagnostic reports), integrating spaCy entity extraction, Pinecone vector search, and a Spring Boot API on AWS with monitoring and guardrails. Demonstrates strong MLOps/orchestration (LangChain, Airflow, Kubeflow/Kubernetes) and a metrics-driven evaluation approach, and partnered with a healthcare operations manager to cut manual review time by 80%.”

Brad Marshall

Screened

Executive Technology Consultant specializing in Microsoft BI and Azure cloud migrations

29y exp

“Has experience working with venture capital firms evaluating target companies for potential acquisitions, focusing on technology maturity, technical stack, and team/human resources assessment.”

Jyothsna V

Screened

Mid-level Backend Software Engineer specializing in Python/FastAPI and cloud-native microservices

USA4y exp

“Backend engineer who evolved Coca-Cola bottlers' Trade Promotion Optimization platform at Coke One North America, building domain-focused microservices in Node.js and Python (Flask/FastAPI) with PostgreSQL. Experienced in multi-tenant security (OAuth2/JWT, RBAC, row-level scoping by bottler/region), API contract/versioning discipline, and Azure DevOps-driven incremental rollouts with strong observability.”

Mrudula Devaguptapu

Screened

Mid-Level Software/AI Engineer specializing in backend systems, data pipelines, and RAG automation

United States3y exp

“Backend engineer with experience modernizing high-traffic subscription and payment systems (TCS) by moving to event-driven Spring Boot microservices with Kafka, adding idempotency/state management to eliminate duplicate processing. Built and scaled FastAPI services for AI automation workflows (360DMMC) with versioned contracts, JWT security, and strong observability, and has led live refactors using feature flags, parallel runs, and data reconciliation.”

Nidhi Sura

Screened

Junior Software Engineer specializing in AI platforms, distributed systems, and cloud infrastructure

Dublin, CA1y exp

“Software engineer with limited robotics background but deep experience building end-to-end document ingestion and image understanding systems, including a CAD-specific pipeline using a custom model to extract components and bounding boxes for user-facing visualization and Q&A. Also brings strong infrastructure/DevOps skills (Docker, Kubernetes, GitHub Actions, Terraform) with emphasis on reliability, cost optimization, and uptime.”

Berkan Özgür

Screened

Senior XR Engineer specializing in spatial computing and cross-platform Unity systems

San Jose, CA9y exp

“XR/Unity developer who built an underwater experience (Visutate) featuring reactive flocking fish that respond to user presence and hand-feeding interactions. Also implemented multiplayer using Unity Netcode, addressing sync challenges via reduced streamed data and client-side prediction; prefers impactful work in startup-style environments.”

Vikram Sandigaru

Screened

Mid-level AI Engineer specializing in AI agents, RAG pipelines, and LLM evaluation

Boston, US3y exp

“Built and shipped production LLM systems at Founderbay, including a low-latency voice agent and a graph-based multi-agent research assistant. Strong focus on reliability in real workflows—hybrid SERP + full-site scraping RAG, grounding guardrails, validation checkpoints, and transcript-driven evaluation—plus performance tuning with async FastAPI, Redis caching, and containerization. Also partnered with a non-technical ops lead to automate post-call follow-ups via call summarization, field extraction, and tool-triggered actions.”

Nagendra Reddy Palugulla

Screened

Mid-level Machine Learning Engineer specializing in LLMs, RAG, and MLOps

Florida, United States4y exp

“Built and shipped a production real-time content moderation platform for Zoom/WebEx-style meetings, combining Whisper speech-to-text with fast NLP classifiers and REST APIs to flag hate speech, bias, and HIPAA-related content under strict latency constraints. Demonstrates strong MLOps/infra depth (Airflow, Kubernetes, Terraform/Helm, observability) and a pragmatic approach to reducing false positives via threshold tuning, context validation, and hard-negative data—while partnering closely with compliance and product stakeholders.”

“Candidate is targeting a CTO Venture Studio role and positions themself as a technical partner to founders rather than a founder personally. They demonstrate strong fluency in early-stage startup evaluation, especially around validating whether a product truly tests the business hypothesis and whether the underlying technology can scale significantly.”

“Senior engineer with experience at Micro Focus/HPE (now OpenText) supporting enterprise customers on monitoring platform deployments, upgrades, and ongoing product use. Brings hands-on expertise in operations agents, agentless integrations, security-related upgrade troubleshooting, and cross-functional escalation with engineering to keep customer environments stable and successful.”