Vetted Containerization Professionals

Pre-screened and vetted.

HK

Mid-Level Backend Software Engineer specializing in Java/Spring Boot microservices on AWS

Frisco, TX4y exp
UberUniversity of Texas at Arlington
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GC

Mid-level Software Engineer specializing in backend microservices and cloud-native systems

USA, USA4y exp
UberTexas A&M University–Kingsville
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SL

Senior Full-Stack Engineer specializing in cloud microservices on AWS

6y exp
AmazonUniversity of Missouri-Kansas City
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SS

Mid-level Backend Software Engineer specializing in FinTech and cloud microservices

Bellevue, WA4y exp
UberAuburn University at Montgomery
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SM

Senior Linux Systems Engineer specializing in Cloud, DevOps, and Kubernetes

New York, NY7y exp
TikTokUniversity of Sindh
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MN

Senior DevOps Engineer / AWS Solutions Architect specializing in Kubernetes and DevSecOps

New York, NY7y exp
UberKabul University
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HS

Senior Full-Stack Engineer specializing in Java microservices and FinTech

San Francisco, CA5y exp
AtlassianUniversity of the Cumberlands
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AA

Senior AI/ML Engineer specializing in GenAI, LLMs, NLP, and MLOps

Manhattan, NY10y exp
AssemblyAI
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AM

Abhishikth Meesala

Screened ReferencesStrong rec.

Mid-level AI/ML Engineer specializing in NLP, Generative AI, and fraud detection

Dallas, TX4y exp
PwCCampbellsville University

At PwC, built and productionized an agentic RAG enterprise search assistant over 6M internal documents (8M embeddings), deployed across AWS and GCP. Drove major retrieval gains (72%→92% precision via BM25+dense hybrid with RRF and cross-encoder re-ranking), reduced hallucinations 30%, achieved <2s latency at 50–60K queries/month, and cut support tickets 30%—boosting adoption to 2,500 users by adding source-cited answers.

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LX

Longyang Xu

Screened ReferencesStrong rec.

Junior Full-Stack Software Engineer specializing in cloud microservices and ML-driven products

Quincy, MA1y exp
GraniteCarnegie Mellon University

Backend engineer with hands-on ownership of Python/Flask microservices and recommendation systems across edtech and telecom. Deployed and operated real-time personalization/recommendation platforms on AWS EKS with Jenkins-based CI/CD, GitOps-style declarative configs, and strong observability practices. Has migration experience moving legacy mixed environments to modern containerized Kubernetes and built Kafka pipelines feeding ML services while managing schema evolution.

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Deepam Ameria - Intern Robotics Software Engineer specializing in autonomy, perception, and control in Los Angeles, CA

Deepam Ameria

Screened

Intern Robotics Software Engineer specializing in autonomy, perception, and control

Los Angeles, CA2y exp
AlphaZCarnegie Mellon University

Robotics software engineer with hands-on experience building autonomy features across perception, planning, and systems integration—most notably for an autonomous lunar rover that detects and geometrically models craters to plan terrain manipulation. Also owned development of an autonomous stair-climbing module for a quadruped robot as an intern, and has real-time motion-planning/IK debugging experience on a Franka Panda using RGB-D (RealSense).

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DT

David Toth

Screened

Senior Software Engineer specializing in backend APIs and regulated industries

Austin, TX10y exp
HumanaUniversity of Texas at Austin

Software engineer with recent hands-on production work across Go, Python, and React/TypeScript, spanning healthcare APIs, compliance systems, and data engineering. Stands out for delivering under ambiguity: replaced a legacy SOAP eligibility service, built a Kafka-based compliance pipeline handling 14,000 events per second, and created a modular banking data pipeline that cut month-end work by 30%.

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OO

Senior DevOps/DevSecOps Engineer specializing in AWS & Azure cloud infrastructure

Fairfax, VA10y exp
Technatomy Digital SolutionUniversity of Lagos

Infrastructure/DevOps-focused engineer working across Linux-based enterprise platforms that include IBM Power/AIX in a broader OpenShift/Kubernetes and cloud ecosystem. Built Azure DevOps CI/CD for containerized deployments and resolved a production deployment failure by tracing ImagePullBackOff to outdated registry credentials in Kubernetes secrets. Uses Terraform (with modular structure) plus Ansible to provision and standardize production environments with pipeline-based validation.

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TG

Junior Software Engineer specializing in full-stack AI systems

Greenwich, CT1y exp
Birdie AICornell University

Sole developer behind BirdieAI, an AI-powered golf booking platform built from the ground up, spanning frontend UX, backend services, AWS infrastructure, and Postgres database management. Worked directly with a cofounder in a startup setting to scope and ship an MVP, then improved production reliability significantly by reducing a key extraction failure from 1 in 15 to 1 in 300 while adding operational safeguards and user-driven product improvements.

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MN

mahesh narne

Screened

Senior Full-Stack Software Engineer specializing in cloud-native microservices and web apps

San Jose, CA3y exp
PayPalUniversity of Central Missouri

Backend-focused engineer building customer support/order-tracking platforms with Java 17/Spring Boot microservices and a React/TypeScript frontend. Deep experience running event-driven systems on Kubernetes (Kafka, Redis, MySQL) with strong observability (Prometheus/Grafana/Splunk), SLOs, and safe deployment practices (feature flags, canaries). Also built an internal monitoring/debugging dashboard that consolidated metrics and logs for on-call engineers and was adopted by other teams to speed incident response.

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VV

vishal varma

Screened

Mid-level Generative AI Engineer specializing in LLMs, RAG, and MLOps

6y exp
CVS HealthUniversity of Bridgeport

Built and deployed a production RAG-based LLM Q&A and summarization platform for internal documents, emphasizing grounded answers with structured prompting and citations to reduce hallucinations. Experienced orchestrating end-to-end LLM workflows with LangChain plus cloud pipelines (Azure ML Pipelines, AWS), and runs iterative evaluation using both metrics (accuracy/hallucination/latency/cost) and real user feedback to drive reliability.

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TA

Tauhid Arah

Screened

Senior DevOps Engineer specializing in AWS cloud platform engineering and Kubernetes

The Bronx, NY12y exp
NETGEARFederal University of Technology Minna

Cloud-focused DevOps/Infrastructure engineer with hands-on AWS high availability, migration cutovers, and production automation. Built Jenkins-based CI/CD pipelines (Git, SonarQube, Artifactory) and manages Terraform IaC with S3/DynamoDB remote state, PR-based reviews, and staged environment promotion; targets $160k base. No direct IBM Power/AIX/PowerHA experience.

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Akashleena Sarkar - Junior Software Engineer specializing in robotics and real-time distributed systems in Mountain View, CA

Junior Software Engineer specializing in robotics and real-time distributed systems

Mountain View, CA2y exp
Intrinsic Innovation LLCUC Santa Cruz

Robotics software engineer focused on low-compute navigation/SLAM: built a 6-DOF SLAM validation pipeline (IMU + 2D LiDAR + ultrasonic) producing ~1cm OctoMap accuracy and deployed it on an Intel Atom by optimizing particle-filter SLAM with a greedy max-likelihood update. Deep ROS 2 experience (executors, composable/lifecycle nodes, QoS, timestamping) plus simulation and deployment tooling (Gazebo C++ plugins, Docker, CI/CD, ROS 2 build farm) and drone navigation work with MAVROS/PX4.

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AD

Aarati Dulal

Screened

Senior Full-Stack Java Engineer specializing in cloud-native microservices

Dallas, TX6y exp
Goldman SachsAvila University

Backend/platform engineer who owned high-volume Java/Spring Boot microservices on AWS (Kafka + RDS/DynamoDB) and has hands-on experience debugging complex production latency incidents across DB, JVM/GC, and async consumers. Also shipped applied AI features for ops, including an LLM-powered log analysis assistant and an incident-response agent with strong safety guardrails (schema-validated tool use, retries/backoff, and human-in-the-loop escalation).

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Rahul Kushwaha - Mid-level Software Engineer specializing in FinTech and scalable microservices in Texas, USA

Mid-level Software Engineer specializing in FinTech and scalable microservices

Texas, USA5y exp
PayPalSanta Clara University

Backend/platform engineer focused on high-traffic financial systems, owning real-time event-driven ingestion and Kafka streaming pipelines using Python/FastAPI, Avro schemas, and AWS services. Has hands-on Kubernetes (EKS) and GitOps/CI-CD experience (ArgoCD/Jenkins) and supported large-scale migrations from legacy VMs to containerized microservices with zero/low-downtime cutovers.

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Hongxi Chen - Intern Software Engineer specializing in distributed systems and backend infrastructure in Beijing, China

Hongxi Chen

Screened

Intern Software Engineer specializing in distributed systems and backend infrastructure

Beijing, China0y exp
Chinese Academy of SciencesUniversity of Nottingham

Backend engineer with deep experience building event-driven logistics systems (orders, warehouse execution, real-time delivery tracking) using Spring Boot/PostgreSQL/Redis and strong observability (Prometheus/Grafana). Led a zero-downtime migration from monolithic MySQL to a sharded architecture for ~2M users with dual-write, checksum validation, and fast auto-rollback, and has strong security expertise including PostgreSQL RLS for multi-tenant SaaS and robust OAuth/JWT handling.

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SP

Satya Pithani

Screened

Mid-level AI/ML Engineer specializing in healthcare and financial analytics

Texas, USA4y exp
Oracle HealthUniversity of Texas at Dallas

ML engineer with production experience across healthcare and fraud domains, including end-to-end ownership of a telecare patient deterioration system at Oracle Health and a GPT-4/RAG fraud reporting solution at Cognizant. Stands out for combining scalable data/ML infrastructure, clinical NLP, and GenAI delivery with measurable gains in model quality and workflow efficiency.

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NC

Senior Full-Stack Engineer specializing in AI and cloud-native applications

Lakeland, FL8y exp
Revscale AIUC Irvine

Built and shipped a production LLM-powered internal developer tool that accelerated code reviews by about 30% while maintaining reliability through modular orchestration, validation, and monitoring. Demonstrates strong practical depth in agent architecture, backend workflow orchestration, and observability for non-deterministic AI systems, with concrete examples of reducing agent errors by 60%.

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