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Vetted Microsoft Azure Professionals

Pre-screened and vetted.

NT

Senior Full-Stack Developer specializing in FinTech microservices

Morristown, NJ8y exp
Valley Bank
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IT

Software Engineering Manager specializing in FDA-compliant medical device software

San Jose, CA16y exp
Imrooj LLC
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MA

Senior Full-Stack Python Developer specializing in Django, FastAPI, and cloud platforms

Matamoras, Pennsylvania9y exp
Weston Chase
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SS

Mid-level AI Engineer specializing in production LLM, RAG, and agentic AI systems

6y exp
Bank of America
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NM

Executive Cybersecurity & Risk Management Leader specializing in FedRAMP, CMMC, and cloud security

Orlando, Florida18y exp
Rise8
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BM

Senior Customer Success Manager specializing in Technical B2B SaaS

San Francisco Bay Area, CA7y exp
Nimble
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SK

Senior Full-Stack Developer specializing in cloud-native FinTech microservices and React

Chicago, Illinois11y exp
Capital One
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SD

Senior Data Scientist specializing in NLP, MLOps, and cloud ML platforms

Westfield Center, OH7y exp
Westfield Insurance
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NZ

Executive IT & Cybersecurity Leader specializing in cloud, infrastructure, and enterprise risk

Dallas, TX11y exp
BGSF
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FH

Senior Software Test Engineer specializing in automation, API, performance, and accessibility testing

New York, New York12y exp
NYC Administration for Children's Services
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AM

Principal Automation Architect specializing in cloud DevOps, microservices, and MLOps

Spring, TX16y exp
SparkSoft
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AT

Senior Technical Support & Sales Enablement leader specializing in cloud security and enterprise infrastructure

San Jose, CA21y exp
Supermicro
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HS

Mid-level Java Full-Stack Developer specializing in cloud-native microservices

Dallas, TX4y exp
Baylor Scott & White
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RG

Senior Full-Stack Java Developer specializing in Spring Boot microservices and cloud platforms

Orlando, FL10y exp
HD Supply
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MS

Senior Full-Stack Java Engineer specializing in microservices, cloud, and enterprise platforms

San Diego, CA9y exp
MedImpact
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AI

Senior DevOps/SRE Engineer specializing in multi-cloud infrastructure and Kubernetes

Chicago, IL11y exp
Northwestern Memorial Hospital
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KR

Senior AI Python Engineer specializing in Generative AI and MLOps

San Francisco, CA8y exp
Silicon Valley Bank
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SM

Sanjay Mamani

Screened ReferencesStrong rec.

Executive Technology Leader specializing in enterprise data, AI, and cloud analytics

Mooresville, USA26y exp
BridgetreeUniversity of North Carolina at Greensboro

25-year builder/operator who has scaled others' visions and led VC-backed startup incubation work (Saltmines). Built Bridgetree’s AI CoE from 0 to 1 and cites $20M+ measurable customer impact, with experience leading 110-person cross-disciplinary teams. Exploring a new venture idea (gotAgentic.ai) focused on agentic AI solutions such as AI-ready data prep, agentic SDLC teams, and front-office automation (scheduling/invoicing).

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BH

Banchode Hari

Screened

Mid-level Full-Stack Developer specializing in microservices and event-driven systems

USA6y exp
T-MobileKent State University

Full-stack engineer with end-to-end ownership of a production customer plan activation and account management flow at T-Mobile, spanning Java/Spring Boot APIs, React frontend, and Docker-based CI/CD deployments. Demonstrated performance/scalability work (query optimization, indexing, caching) and measured success via improved retrieval speed and reduced support tickets.

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RM

Rahul Manne

Screened

Mid-Level Software Engineer specializing in .NET, Azure, and ML automation

Worcester, MA5y exp
Johnson & JohnsonClark University

JavaScript/React/TypeScript engineer with hands-on open-source experience improving a hooks utility library—fixed a reported async race condition that reduced unexpected re-renders and added a debounced callback hook that became widely used. Brings a production-minded approach to performance and abstractions (APM/metrics-driven, DB/caching focus) with strong testing, documentation, and community support practices.

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MG

Mike Gardiner

Screened

Technology Executive / Engineering Director specializing in AI-driven platform transformation

Lehi, UT12y exp
VivintWeber State University

Built a 0-to-1 iOS mobile gardening application that helps users plan, track, and harvest crops with pest control guidance, weather, and climate-zone-based planting date recommendations. Demonstrated strong customer discovery and MVP-first product execution, including a major data challenge: compiling US climate zone data for every ZIP code from widely dispersed public sources into an app-ready database.

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RG

Mid-level Python Developer specializing in APIs, data engineering, and cloud-native systems

Remote, USA4y exp
Marsh McLennanFlorida Atlantic University

Backend engineer (Marsh McLennan) who evolved a high-volume claims automation pipeline in Python, emphasizing thin APIs with background job processing, strong validation/retries, and production-grade observability. Experienced in secure FastAPI API design (centralized JWT/RBAC), multi-tenant Postgres/Supabase-style row-level security, and low-risk refactors using parallel runs and feature flags; targeting founding-engineer scope roles.

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CH

Mid-level AI/ML Engineer specializing in healthcare, risk modeling, and MLOps

Milwaukee, WI3y exp
UnitedHealth GroupUniversity of Wisconsin–Milwaukee

Robotics software engineer who built a ROS Noetic-based perception-to-control stack for a pick-and-place robotic arm, integrating OpenCV/TensorFlow vision with motion planning and PID tuning. Demonstrated strong real-time debugging skills (rosbag, queue/latency fixes) and experience deploying reproducible robotics environments with Gazebo simulation, Docker, and GitLab CI.

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VJ

Vedang Jadhav

Screened

Mid-Level Software Engineer specializing in cloud-native microservices on AWS

New York City, NY5y exp
CitigroupIndiana University Bloomington

Backend engineer with experience across healthcare and fintech platforms (Anthem, Citia) building high-throughput Python microservices with strong compliance/security focus (HIPAA, tenant isolation). Has integrated ML workflows into production systems (ResNet embedding-based image similarity) using async pipelines (Celery/Redis) and AWS (Lambda/S3/ECS), delivering measurable performance and fraud/content-integrity improvements at scale.

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