Vetted Microsoft Azure Professionals

“Forward Deployed Engineer at EasyBee AI who productionized a self-storage customer’s multi-agent LLM system end-to-end—rebuilding it with LangGraph/CrewAI, integrating with real property management + CRM systems via an MCP server, and adding observability/guardrails for reliable daily use. Experienced in live troubleshooting of agentic workflows, developer demos/workshops (including an open-source project, MerryQuery), and partnering with sales to close deals through customer-specific technical demos and fast integration feedback loops.”

“Backend-focused engineer who built an academic AI voice assistant with a Python microservice-style backend (speech recognition, spaCy-based NLP, and Kafka-driven automation) optimized to sub-500ms latency. Also has Sodexo internship experience deploying containerized services across Kubernetes/AWS ECS/Azure using ArgoCD GitOps, including solving config drift and secret-management challenges and supporting cloud-to-on-prem migrations with blue-green rollouts.”

“Full-stack engineer from Clairvoyant who led end-to-end delivery of a cloud-native, event-driven platform: Spring Boot microservices + Kafka real-time streams with an Angular UI, migrated and containerized on AWS, and automated CI/CD with Jenkins/Maven/Git. Demonstrates depth in distributed consistency challenges (partitioning, consumer lag/duplicates) and database performance tuning across SQL/NoSQL under heavy workloads.”

“Data scientist who has built production LLM agents (GPT-4o + LangChain + RAG) to automate analyst-style ad hoc CSV analysis with guardrails and GPT-as-a-judge evaluation. Also delivered an explainable healthcare NLP system for ICD code classification by collaborating closely with clinicians, using a hybrid rule-based decision tree + BERT model to reach 97% accuracy and cut manual review time.”

“Full-stack engineer operating in early-stage, high-velocity environments (OpGov.AI/UST Calibrate) who ships production Next.js App Router features end-to-end (RSC, Server Actions, SEO, RBAC, caching) and owns performance post-launch. Demonstrates strong data/infra depth—designed Postgres JSONB-based event models for DevOps/DORA analytics and tuned queries from ~2s to <50ms, plus built durable ingestion workflows with retries and idempotency on Azure.”

“Backend/AI engineer who has built production LLM orchestration and agentic workflow systems in Python/FastAPI on Kubernetes across AWS/Azure. Demonstrated strong reliability engineering by debugging a real-world memory retention issue that caused latency spikes/timeouts, and strong data/performance chops with a PostgreSQL optimization that cut query latency from ~1.2s to ~15ms. Targets roles building scalable, guardrailed AI-driven workflow automation with robust observability and human-in-the-loop controls.”

“Data science professional who has built a production RAG-based LLM question-answering system ("Flash Query") to deliver fast, accurate answers over large document collections, focusing on retrieval quality and grounded responses. Also collaborates with non-technical retail/jewelry stakeholders to turn business questions into predictive models and dashboards for decision-making.”

“Full-stack engineer who has shipped and operated generative-AI chat/QA features end-to-end, including a RAG-based pipeline with guardrails and cost/latency monitoring in production. Experienced with React/TypeScript + Node/Postgres architectures, Dockerized deployments to AWS (EC2) via GitHub Actions CI/CD, and building reliable ingestion/ETL systems with idempotency, backfills, and reconciliation.”

“Backend engineer with experience building an end-to-end civic tech AI platform that ingests city council meeting videos, transcribes them with Whisper, and enables natural-language Q&A via a LangChain/FAISS RAG pipeline. Demonstrated strong systems thinking by tuning retrieval for accuracy/latency/memory (cutting response time ~3s→1s and memory ~500MB→25MB) and by safely migrating an ERP from monolith toward services using dual writes, reconciliation, and idempotency to protect financial workflows.”

“Built and deployed a production RAG-based multilingual analytics assistant for healthcare operations, enabling non-technical teams to query claims/EHR and risk metrics with grounded explanations. Demonstrates strong end-to-end LLM system engineering (retrieval tuning, re-ranking, hallucination controls, verification layers) plus workflow orchestration (Airflow/Composer/Step Functions) and stakeholder-driven iteration via prototypes and dashboards.”

“Software/product engineer who owns customer-facing internal platforms end-to-end, with deep experience building data pipeline health and data quality tooling (near-real-time alerting and ops dashboards). Strong in React/TypeScript + Python REST architectures and microservices with RabbitMQ, emphasizing reliability patterns (idempotency, DLQs, correlation IDs) and fast, safe iteration via feature flags, testing, and observability.”

“Unity developer who built a distinctive "truth-seeing" gameplay mechanic that shifts the world to monochrome while selectively revealing hidden/deceptive objects, using an overlay camera and draw-order fixes to meet tricky rendering constraints. Also has Photon PUN experience delivering a synchronized mixed-reality tabletop construction visualization where a host controls shared model transforms, layer toggles, and can transfer host control.”

“AI/ML engineer who has shipped production systems across computer vision and conversational agents: built a YOLOv8-based wheel fitment pipeline at a Techstars-backed automotive startup, focusing on sub-second latency, monitoring, and robust fallback mechanisms that drove 2–3x page view growth and +5–6k users. Also built a voice-based interview platform orchestrating Deepgram + GPT-4 Mini + OpenAI TTS with FSM-driven reliability, and has hands-on RAG experience (LangChain, hybrid retrieval, cross-encoder reranking, custom pseudo-query generation).”

“Currently at ProShare and reports building an AI/LLM-powered system deployed to production, aimed at helping with status-related difficulties and reducing misunderstandings across transactions. Also cites prior collaboration at Porsche with marketing teams, focusing on translating marketing goals into technical requirements and communicating solutions clearly to non-technical stakeholders.”

“Built and deployed a production RAG-based LLM assistant that answers day-to-day operational questions from internal PDFs/SOPs, with strong emphasis on data consistency (metadata versioning, confidence thresholds, conflict handling) and low-latency retrieval at scale. Experienced designing and orchestrating multi-agent LLM workflows (retrieval/validation/generation) and pipeline orchestration for ingestion/embedding/vector-store updates, plus iterative delivery with non-technical operations/business stakeholders.”

“Frontend-focused engineer (Shahroz) who has rebuilt and modernized products end-to-end, including a FitTech dashboard redesign from scratch with standardized tooling (ESLint/Prettier, Husky + conventional commits, unit tests, PR validation). Has delivered complex React + TypeScript dashboards involving real-time live streaming and analytics, and shipped an e-commerce PDP with integrations like Contentful and social feeds using an MVP-first, sprint-based process.”

“Built and operated large-scale biodiversity/ecological research platforms, integrating 50+ heterogeneous global datasets into a unified BIEN 3 schema on PostgreSQL/PostGIS and improving data consistency by 35%. Strong production engineering background (Linux monitoring, CI/CD performance gates, Docker on AWS/Azure) plus applied AI work building a Python RAG system (0.90 precision) and halving latency with Elasticsearch.”

“Built an LLM-driven MLOps agent at SBD Technologies that automated an EV-charging prediction workflow end-to-end, integrating with real-time Kafka/FastAPI systems supporting 120K+ chargers at 99.99% event delivery. Addressed frequent schema drift by implementing SQLAlchemy/Flyway validation (60% reduction in drift issues) and deployed as Kubernetes microservices with GitHub Actions CI/CD; also has Airflow-based ingestion/crawling experience into Snowflake and stakeholder-facing delivery via a Fleetcharge PWA.”

“Backend engineer who owned the API layer for an AI trust/analytics dashboard (trust scores, stability checks, public verification endpoints) using Python/FastAPI and Postgres. Has hands-on DevOps experience deploying FastAPI and Node.js services to AWS Kubernetes with GitHub Actions + ArgoCD GitOps, plus Kafka-based real-time event streaming and careful staged migration practices (shadow traffic/dual writes, rollback planning).”

“Built and deployed ForensicLLM, a local domain-specific LLaMA-3.1-8B model for digital forensic investigators using RAFT + RAG over 1000+ curated research papers, with citation-aware responses and rigorous evaluation (BERTScore/G-Eval). Deployed via vLLM and Docker and validated through a chatbot survey with 80+ participants; published at DFRWS EU 2025.”

“Full-stack developer who built an end-to-end billing/allocation/payment and reporting system used daily by a major film-industry union, including queuing-based check assignment, admin auditing, data cleanup tools, and an external reports portal. Also delivered a factory production scheduling/analytics app for a lock manufacturer, and typically implements APIs in C#/.NET with DTO shaping and pub/sub messaging for microservices consistency.”

“Entrepreneur with 20+ years in the recruiting industry building a Salesforce-based CRM tailored to track candidate outreach from initial identification (positioned as a differentiated alternative to traditional ATS workflows). Previously launched a small consulting company after spotting unmet technical needs among small medical practitioners, emphasizing branding and relationship-driven business development.”

“Cloud/DevOps-focused engineer with hands-on experience building Azure DevOps CI/CD pipelines for containerized applications deployed to AKS, including security scanning, approvals, versioned artifacts, and rollback. Also implemented Terraform-based IaC for Azure (VNets/subnets/NSGs/AKS) with modular design, remote state/locking, and drift detection; resolved a real deployment outage caused by an Azure RBAC permission change.”

“Backend-leaning full-stack engineer in fintech/payments who shipped an end-to-end Stripe payments + webhook system for a financial microservices platform, emphasizing ledger accuracy via idempotency, transactional writes, retries, and DLQs. Also delivered a real-time React/TypeScript payment status dashboard informed by user interviews, and improved production performance by 35% p95 latency through PostgreSQL tuning and Redis caching on AWS.”