Vetted Kubernetes Professionals

Pre-screened and vetted.

AS

Senior Software Engineer specializing in Healthcare AI and FinTech platforms

Baton Rouge, LA13y exp
GoogleLouisiana State University

Google Health engineer who owned and shipped an AI-powered clinical insights dashboard and NLP clinical note extraction service end-to-end (React/Next.js frontend; Python/Node microservices on GKE; TensorFlow transformers; BigQuery analytics). Demonstrated strong production rigor (CI/CD, testing, observability, guardrails for sensitive data) and delivered measurable outcomes including 30% faster diagnostics, 40% less manual documentation, 15% higher adoption, and 25% lower ops costs.

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BH

Senior Full-Stack Software Engineer specializing in AI/LLM and cloud platforms

9y exp
ResultStackStony Brook University
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CF

Senior Full-Stack AI Engineer specializing in generative AI and cloud platforms

Houston, TX11y exp
AdobeTexas Tech University
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CW

Senior DevSecOps Engineer specializing in secure cloud CI/CD and Kubernetes

Remote9y exp
CommureCarnegie Mellon University
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David Song - Senior Full-Stack Software Engineer specializing in cloud, payments, and telehealth in Baltimore, MA

Senior Full-Stack Software Engineer specializing in cloud, payments, and telehealth

Baltimore, MA13y exp
AmazonUCLA
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AW

Senior Full-Stack Engineer specializing in microservices, data pipelines, and cloud platforms

Remote14y exp
MetaUniversity of Chicago
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JW

Staff Software Engineer specializing in SaaS platforms across Healthcare and FinTech

Katy, TX11y exp
AmwellUniversity of Texas at Austin
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JC

Staff Software Engineer specializing in cloud-native healthcare and payments platforms

Remote14y exp
AmazonUniversity of Texas at Dallas
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BK

Senior Software Engineer specializing in distributed systems and cloud infrastructure

New York, NY8y exp
GoogleNYU Tandon School of Engineering
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CB

Senior Software Engineer specializing in cloud-native microservices and large-scale backend systems

Houston, TX10y exp
GoogleUniversity of Texas at Austin
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EL

Senior Full-Stack AI Engineer specializing in LLM/RAG and production ML platforms

Chicago, IL9y exp
Ardan LabsUniversity of Illinois Urbana-Champaign
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SS

Saleem Sultan

Screened ReferencesStrong rec.

Director-level Product & Engineering Leader specializing in AI/ML, cloud platforms, and digital transformation

Dallas, TX10y exp
HCSCCornell University

Senior engineering/technology leader who has defined and delivered a multi-year roadmap to modernize platforms and embed AI, leading global teams through cloud-native and microservices migrations on AWS/Azure. Demonstrated measurable outcomes including 99.99% uptime, 40% fewer incidents, 25% faster delivery, 5x scalability, and $30M in new business opportunities, while scaling a 100+ person distributed org with strong OKR-driven execution and mentorship culture.

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Nicholas Ogura - Executive Platform & Security Engineering leader specializing in multi-cloud Kubernetes and FinTech in San Diego County, USA

Nicholas Ogura

Screened ReferencesStrong rec.

Executive Platform & Security Engineering leader specializing in multi-cloud Kubernetes and FinTech

San Diego County, USA18y exp
Terrace

Startup-focused infrastructure/security leader who stepped into head of engineering and re-platformed an entire product end-to-end in 3 months to meet launch. In crypto/fintech, recognized the market-data system as an ETL/data product and rebuilt it as a separable, securely accessible platform—prompting inbound interest within a week—while advocating an open-source-first observability stack (Prometheus/Grafana/Loki) to avoid vendor lock-in.

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JM

Mid-level AI/ML Engineer specializing in LLM fine-tuning, RAG, and scalable inference

Bay Area, CA5y exp
MetaSoutheast Missouri State University

ML/LLM engineer who built and shipped an LLM-powered internal knowledge assistant at Meta, focusing on production-grade RAG to reduce hallucinations and improve trust. Deep experience with scaling and serving (FSDP/DeepSpeed/LoRA, Triton, Kubernetes autoscaling) and reliability practices (Airflow retraining, MLflow versioning, monitoring with rollback), including sub-100ms latency and ~35% GPU memory reduction.

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VI

Vishanth Iyer

Screened

Senior AI/ML Engineer specializing in LLMs, multimodal AI, and scalable MLOps

San Jose, CA10y exp
NVIDIASanta Clara University

ML/NLP engineer with experience at NVIDIA and Cruise building production-grade AI systems across genomics/biomedical research and autonomous vehicle data. Has delivered multimodal LLM pipelines, large-scale entity resolution, and hybrid semantic search (BERT embeddings + FAISS + Elasticsearch), with measurable impact (≈40% accuracy/retrieval gains; ≈30% data consistency improvement) and strong MLOps practices (Kubernetes, CI/CD, MLflow, Prometheus/Grafana).

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NS

Nish Sharma

Screened

Executive Engineering Leader specializing in FinTech, Payments, and GenAI transformation

Brooklyn, New York12y exp
OnePayUniversity of Illinois Urbana-Champaign

Fintech product builder focused on AI-native opportunities; recently helped their company operationalize LLMs in customer service and bank ops by creating systems to continuously improve prompts and evaluations. Also drove growth by identifying hooks in a major American retailer distribution channel and integrating into the retailer’s payment flows to become a key part of the user funnel.

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Brian Gomez - Senior Machine Learning Engineer specializing in AI/ML, NLP, and computer vision in United States

Brian Gomez

Screened

Senior Machine Learning Engineer specializing in AI/ML, NLP, and computer vision

United States12y exp
McKinsey & CompanyCornell University

McKinsey & Company ML/NLP practitioner who builds production-grade AI systems across sectors (notably healthcare and finance), including RAG/LLM solutions, entity resolution pipelines, and embedding-powered search with vector databases. Demonstrated measurable impact (40% reduction in data duplication) and strong MLOps/data workflow practices (Airflow, MLflow, Spark, AWS/GCP, Prometheus, CI/CD).

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HL

Huiren Li

Screened

Senior Backend/Full-Stack Engineer specializing in scalable microservices on AWS

Menlo Park, CA7y exp
UberUniversity of Illinois Urbana-Champaign

Backend/data engineer with production experience at Uber building a near real-time driver rewards service on AWS (FastAPI, PostgreSQL, Redis) with strong reliability and concurrency controls. Also delivered AWS Lambda/ECS containerized deployments with GitHub Actions CI/CD and cost governance, built AWS Glue ETL with schema-evolution handling, and drove a ~10x SQL performance improvement while owning incident response via CloudWatch.

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Sri Yogesh Dorbala - Engineering Manager / Tech Lead specializing in large-scale distributed systems in Seattle, WA

Engineering Manager / Tech Lead specializing in large-scale distributed systems

Seattle, WA8y exp
DoorDashPurdue University

Software engineer focused on personalization and data/ML infrastructure who built a GenAI/LLM-driven carousel ranking system end-to-end, delivering a reported 6–7% order-rate lift. Also designed large-scale personalization ETL (15PB for ~100M users) and created a custom Airflow operator to integrate with Databricks under enterprise version constraints, with hands-on on-call and data-quality reliability improvements.

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DG

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

Seattle, WA5y exp
ShopifySaint Louis University

NVIDIA engineer who built and shipped a production LLM-powered enterprise knowledge system (summarization, transcription, and Q&A) that cut document retrieval time ~30%. Deep hands-on experience with RAG (FAISS/Pinecone), GPU-accelerated microservices on AWS, and reliability/safety practices (Guardrails AI, prompt A/B testing, canary releases) plus strong MLOps orchestration across Airflow, Step Functions, and Kubernetes GitOps.

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Maria Li - Entry-Level Firmware Engineer specializing in embedded–cloud systems in New York, NY

Maria Li

Screened

Entry-Level Firmware Engineer specializing in embedded–cloud systems

New York, NY2y exp
SamsaraUC Berkeley

Backend engineer at Samsara with prior Amazon internship experience; built an internal Python chatbot for documentation discovery with a full security model (authn/authz and credential-based response filtering) in a sensitive environment. Currently works on dashcam/device-backend systems, including feature-flagged migrations for audio alert behavior and resilient real-time gRPC streaming under unreliable cellular connectivity, while actively monitoring Buildkite/Toolshed CI/CD rollouts.

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Chang Qian - Senior Backend/Infrastructure Engineer specializing in large-scale integrity and content systems in Menlo Park, CA

Chang Qian

Screened

Senior Backend/Infrastructure Engineer specializing in large-scale integrity and content systems

Menlo Park, CA10y exp
FacebookCarnegie Mellon University Silicon Valley

Backend/platform engineer who built Bilibili’s "Avalon" content moderation platform from a vague CEO mandate into a company-wide service (Go, gRPC, Kafka), including on-call, metrics, transparency tools, and multi-site resiliency work. More recently at Meta, scaled a high-traffic mistake-prevention platform by introducing capacity levers (prefiltering, caching, log sampling, fanout limits) and navigating org-wide constraints, including debugging a rule-engine threading bottleneck.

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Sahitya Thota - Staff/Tech Lead Software Engineer specializing in identity, data platforms, and cloud systems in Fremont, CA

Sahitya Thota

Screened

Staff/Tech Lead Software Engineer specializing in identity, data platforms, and cloud systems

Fremont, CA20y exp
MetaOsmania University

Engineering leader/player-coach who built and owned end-to-end sales-facing data products, including a 360° advertiser insights platform and a sales AI agent for natural-language access to insights. Demonstrated strong architecture and reliability chops (event-driven redesign to eliminate Hive-query throttling; batching/caching to reduce fan-out) plus incident ownership around ads attribution consistency. Also has 0→1 experience building graph-based recommendation/matching systems with explainability and tight user feedback loops.

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