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Vetted AWS Professionals

Pre-screened and vetted.

PS

Mid-level Machine Learning Engineer specializing in IoT, edge AI, and enterprise ML

Texas, USA5y exp
AllstateTexas A&M University-Corpus Christi

Built and productionized an LLM/RAG question-answering service over technical documentation, focusing on retrieval quality (reranking + IR metrics), latency, and scaling. Experienced orchestrating end-to-end ETL/ML workflows with Airflow/Prefect/AWS Step Functions and improving reliability via parallelism, retries, and shadow testing. Also delivered an explainable healthcare risk-flagging classifier with a stakeholder-friendly dashboard for a non-technical program manager.

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NS

Navya Sureddy

Screened

Mid-level Full-Stack Developer specializing in Angular/React and Spring Boot

Columbus, IN5y exp
CumminsUniversity of Missouri-Kansas City

Full-stack engineer with experience at Cummins owning production features end-to-end (React/TypeScript + Node + Postgres) and operating them in AWS (EC2/RDS/S3/IAM) with CloudWatch-based observability. Also built resilient ETL and third-party integrations, including an AWS Glue–S3–Redshift pipeline hardened with validation, idempotent UPSERTs, retries/backfills, and quarantine handling to prevent bad or duplicate data.

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AM

Aravind Mohan

Screened

Mid-level Backend Software Engineer specializing in reliable APIs and tool-using systems

Seattle, WA5y exp
Swirl LLCUniversity at Buffalo

Backend/AI workflow engineer who built a production event-personalization service (FastAPI + AWS Lambda) and solved real-world reliability/latency issues with deterministic routing, caching, and query/index optimization. Also built an end-to-end Gmail-based job application tracking agent using a lightweight RAG pipeline with Gemini, strong guardrails (Pydantic schemas, confidence thresholds), and offline regression tests to prevent drift and hallucination-driven data corruption.

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SS

Sumit Sahu

Screened

Mid-level Machine Learning Engineer specializing in computer vision and MLOps on GCP

Atlanta, GA4y exp
NCR VoyixUniversity of Georgia

ML/AI engineer who deployed a real-time, edge-based computer-vision pipeline for produce recognition in retail self-checkout to reduce shrink. Demonstrates strong end-to-end production chops: multi-camera data calibration/sync, ranking-based modeling for fine-grained classes, latency-focused optimization, and continuous A/B testing/monitoring with guardrails. Experienced with ML orchestration (Kubeflow Pipelines, Airflow) and CI/CD via GitHub Actions, and collaborates closely with store operations to make interventions usable in the checkout flow.

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SV

Staff-level Customer Success & Support Engineer specializing in enterprise monitoring and workflow automation

Berthoud, CO22y exp
CollibraCalifornia State University, Long Beach

Frontline support engineer in IT infrastructure monitoring (Micro Focus/HPE, now OpenText) who evolved into a hybrid support/TAM role. Experienced advising security-conscious customers (government/banking) on TLS upgrades and vulnerability response, coordinating dev and sales to meet regulatory deadlines while providing practical interim mitigations and clear customer communications.

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DS

Darren Scott

Screened

Executive CTO specializing in data platforms, DevOps, and regulated FinTech

Denver, CO15y exp
Clean Energy Credit UnionUniversity of Wyoming

Startup and early-internet product leader with repeated experience building in new companies and executing pivots. Helped transform a web-based calendar business into a CMS + RBAC platform that became best-in-breed for US K-12 organizations within about three years, emphasizing ROI-driven prototyping and market validation to conserve resources.

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SK

Shri Krishna

Screened

Mid-level Full-Stack Developer specializing in modern web apps and DevOps

Chicago, Illinois5y exp
MediaoceanUniversity of Illinois Chicago

Product-focused full-stack engineer (70% application-layer) who has shipped multi-tenant RBAC for a formerly single-tenant platform, cutting infrastructure costs by 50%. Built high-impact customer-facing features including analytics dashboards (40% retention lift) and a React/TypeScript scheduling grid that reduced navigation time by 60% and setup time by 80%, with solid AWS operations and Postgres performance tuning experience.

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SY

Sarthak Yadav

Screened

Intern AI/ML Engineer specializing in NLP, computer vision, and reinforcement learning

USA1y exp
Alien AttorneyUniversity at Buffalo

Built an Arduino-based obstacle-avoiding robot using sonar/laser sensors and improved performance from 0.60 to 0.87 accuracy through sensor-fusion thresholding and iterative tuning. In an internship, optimized a legal-document NLP pipeline by switching to a distilled/quantized transformer and offloading inference to a GPU-backed Flask service, cutting inference time by 40%+ without added infrastructure spend.

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AB

Mid-level Software Engineer specializing in Data Science and Machine Learning

Arlington, Virginia4y exp
ElevateMeGeorge Washington University

Robotics/AV perception engineer who built a semantic-segmentation road detection system and integrated it into a ROS-based real-time pipeline (ROS bag camera feed to live monitor) achieving ~12 FPS. Strong in practical deployment work: solved multi-library versioning issues (ROS/OpenCV/TensorFlow), containerized the stack with Docker, and optimized inference by shifting runtime to C++ for large latency gains on NVIDIA hardware.

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DA

Danish Asim

Screened

Mid-Level Full-Stack Engineer specializing in cloud-native e-commerce and AI/ML systems

Dearborn, MI3y exp
University of MichiganUniversity of Maryland, College Park

Full-stack engineer with strong ownership in fast-moving environments: designed and shipped a pre-order/campaign inventory system (NestJS + Strapi + Datadog) that freed 34% warehouse space and reduced stock risk to ~5.7%. Also built rapid, high-impact logistics features (Spot Sales) that drove last-mile cost to ~0 in ~40 days, and has hands-on AWS/Terraform/CI-CD experience including deploying a global RAG system with Pinecone, Datadog, and PagerDuty.

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DB

Deepak Bantu

Screened

Mid-level QA Automation Engineer specializing in healthcare applications

Remote, USA5y exp
WalgreensUniversity of Colorado Denver

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.

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NB

Nilesh Bhoi

Screened

Mid-Level Software Engineer specializing in full-stack web apps and real-time systems

Austin, TX3y exp
eHealthSyracuse University

Software engineer who has owned and improved a customer-facing quote flow in a Vue/Nuxt app, using production observability to reduce latency and improve reliability via caching and request-handling fixes. Also shipped an internal LLM Q&A tool using embeddings + RAG over approved company docs and past support tickets, with guardrails, logging, and an evaluation loop that drove retrieval/prompt improvements. Seeking ~$110k base and requires H1B transfer sponsorship.

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VK

Mid-level AI/Machine Learning Engineer specializing in Generative AI, NLP, and MLOps

Saint Louis, MO6y exp
EquifaxWebster University

Built a production LLM/RAG document analysis system for large financial documents (credit reports/PDFs) to help business analysts extract insights faster. Implemented end-to-end pipeline orchestration with LangChain, vector search (e.g., FAISS), and hallucination controls (context grounding, similarity thresholds, and no-answer fallback), delivered as a Dockerized Python API.

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AS

Senior Technology & Product Development Leader specializing in cloud, data platforms, and scaling teams

Miami, FL22y exp
Gambling.com GroupHawaii Pacific University

Has worked at a startup within an incubator program and is a certified mentor with a startup mentorship non-profit focused on early-stage/pre-funded companies. Not currently seeking to found a company or take equity-only roles, but open to working at very early-stage companies (pre-launch/pre-revenue/pre-funded).

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OS

Omkar Sutar

Screened

Mid-level Full-Stack Developer specializing in cloud-native healthcare platforms

CA1y exp
Molina HealthcareUniversity of the Pacific

Full-stack engineer in healthcare and enterprise analytics who has shipped event-driven, near-real-time systems (Spring Boot microservices + Kafka + AWS) and large-scale patient/provider portals (50k+ users). Strong in production reliability and performance—measurably reduced claims latency (27%), cut support tickets (25%), and handled real AWS scaling incidents end-to-end. Also built a Python REST control plane for SDN routing integrated with external reinforcement learning agents.

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AG

Amie Gibson

Screened

Senior Geospatial Developer specializing in GIS automation, elevation/LiDAR, and AI-enabled apps

Sand Springs, OK27y exp
FEMAFlorida Institute of Technology

Built and monetized an object-identification app end-to-end (FastAPI backend, HTML/JS frontend, SQLite→Postgres, auth, and an iOS wrapper via Capacitor/Xcode with Apple privacy/policy compliance). Also productionized an AI-native geospatial metadata/QA assistant using LLM+RAG plus deterministic Python validation, measuring impact via time-to-first-pass review and rework rate, and has experience modernizing legacy GIS workflows and delivering across USDA/FEMA-style teams with disciplined Jira-based execution.

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YR

Mid-level Java Full-Stack Developer specializing in enterprise healthcare and financial services

4y exp
CommonSpirit HealthUniversity of Missouri-Kansas City

Built and shipped a production LLM-powered agent for supply chain operations that integrates ERP data and automates multi-step decision-making with tool calling, state management, and structured JSON outputs. Emphasizes production reliability (guardrails, fallbacks, monitoring, idempotency) and reports strong business impact: 40% faster decisions, 30% higher throughput, and 25% efficiency gains.

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HP

Hansitha P

Screened

Mid-level Data Engineer specializing in scalable ETL/ELT and real-time streaming pipelines

USA4y exp
CVS HealthUniversity of Cincinnati

Built and shipped a production LLM-powered customer support agent for an EV charging platform using RAG plus internal APIs, automating session/payment issues and ticket routing. Emphasizes production readiness via guardrails, schema validation, state-machine orchestration, monitoring, and continuous evals, delivering a reported 35–40% reduction in support tickets and improved customer satisfaction.

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RS

Mid-Level Software Engineer specializing in backend microservices and Healthcare IT

Redmond, WA3y exp
CVS HealthUniversity at Buffalo

Application-focused full-stack engineer in the clinical/health domain who shipped an LLM-powered clinical note summarization workflow end-to-end (FastAPI + Postgres + Kafka workers + React/TypeScript UI) with strong attention to security, auditability, and clinician trust. Has hands-on AWS/EKS operations experience and has resolved real production latency/scaling issues through async processing, query/index tuning, caching, and horizontal scaling.

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DB

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

Kansas, null5y exp
Cardinal HealthUniversity of Central Missouri

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.

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MS

Director of Technology Transformation specializing in ERP, Cloud & Cybersecurity

India23y exp
WWFMaharshi Dayanand University

Senior technology leader focused on joining existing organizations to build and scale products rather than founding at all costs. Has turned a recurring manual data-process bottleneck into a production platform by validating via user interviews, integrating with legacy systems through phased decoupling, and improving reliability with strong data validation/observability while driving cross-team adoption.

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AA

Junior Software Engineer specializing in cloud, DevOps, and applied AI security

West Lafayette, Indiana3y exp
Freight PinsPurdue University

Founding engineer who built a multi-tenant AWS backend from scratch focused on ultra-fast, configuration-driven client onboarding and low operational cost. Automated tenant provisioning/deployments with Terraform + GitHub Actions (new client infra in ~13 minutes) and scaled to 62 production clients handling ~75k requests/day without a major rewrite. Hands-on with migrations (DynamoDB->MongoDB), reliability/observability, and performance tuning (indexes, Redis, queueing, connection management).

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HS

Hy Serure

Screened

Executive Technology Leader & Architect specializing in enterprise digital transformation

Oakhurst, NJ29y exp
Stanley Black & DeckerBaruch College

Longtime S-Corp founder (20+ years) who evolved from running a web agency to becoming a Shopify expert contracted by agencies/brands to upskill teams and lead enterprise eCommerce builds. Recently built and launched a payment-links/QR-code web app in weeks that gained 20 users on day one without advertising; now looking to pivot toward building a scalable product business not tied to hourly contracting.

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SN

Senior Software Engineer specializing in Golang microservices and IAM/SSO

Dallas, TX6y exp
HCLTechUniversity of Texas at Arlington

Backend engineer with experience at DigitalOcean and BNY Mellon, specializing in secure, highly available authentication and API platforms. Built an enterprise SSO system integrating Okta via OIDC with resilience patterns (gRPC contracts, circuit breakers, Kafka) and strong encryption, and led a careful monolith-to-Golang microservices migration using shadow traffic, dual writes, and feature flags to preserve data integrity.

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