Vetted Java Professionals

Pre-screened and vetted.

SU

Principal/Staff Engineer specializing in platform architecture, AI/ML, and distributed systems

18y exp
WorkWise AIGeorgia Tech
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EB

Senior Software Engineer specializing in cloud-native backend systems

San Francisco, CA8y exp
BoxUC Berkeley
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NM

Mid-level systems researcher and engineer specializing in distributed storage and operating systems

Pittsburgh, PA8y exp
Carnegie Mellon UniversityCarnegie Mellon University
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MC

Senior Software Engineer specializing in AI for Healthcare and Enterprise SaaS

Seattle, WA9y exp
Amazon
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Rodolfo Garcia - Senior QA Test Analyst specializing in game and service testing in Los Angeles, CA

Rodolfo Garcia

Screened ReferencesStrong rec.

Senior QA Test Analyst specializing in game and service testing

Los Angeles, CA11y exp
NetflixLos Angeles Mission College

Game QA/automation tester with experience at Blizzard, Bossfight Entertainment, and Netflix, spanning manual-to-automation transitions, Selenium/C# UI automation, and CI/CD nightly reporting via TestRail. Known for an end-user-driven test strategy, strong defect isolation (including crash dumps), and cross-functional test planning that influenced multiplayer UX/design decisions.

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Thazim Banu Shaffee - Engineering Manager specializing in payments, risk, and high-scale distributed systems in San Jose, CA

Thazim Banu Shaffee

Screened ReferencesStrong rec.

Engineering Manager specializing in payments, risk, and high-scale distributed systems

San Jose, CA14y exp
PayPalVellore Institute of Technology

Engineering leader/player-coach on a risk core transaction platform (payments/branded checkout) who led major migrations from a monolithic stack to microservices, including API contract redesign and performance improvements (reported ~500ms latency reduction). Experienced running high-stakes production incidents (upgrade-related outage/degradation) end-to-end with RCA and rollout-process changes, and has accelerated delivery via documentation/tooling (audit sign-off cycle reduced from ~3 sprints to ~1).

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DN

David Neiman

Screened

Mid-level Robotics Researcher specializing in motion planning and vehicle routing

13y exp
Carnegie Mellon UniversityCarnegie Mellon University

CMU robotics PhD/PhD researcher and former CMU Robotics Club project lead who built a novel Bayes-filter-based system to localize within music so robotic instruments can follow a human’s tempo in real time. Also works on simulation-heavy multi-agent vehicle routing with traffic-signal scheduling, optimizing for real-time performance via profiling, multithreading, and neural-network surrogates for signal control.

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AS

Junior Data Scientist specializing in LLM agents, RAG, and reinforcement learning

Pittsburgh, PA1y exp
McKinsey & CompanyCarnegie Mellon University

McKinsey practitioner who built and deployed production LLM systems for consultants/clients, including a Power BI-integrated multi-agent chatbot (RAG + text-to-SQL + formatting) with custom Python orchestration, verification loops, and a 100+ case eval set achieving ~95% consistency. Also delivered a taxonomy-mapper agent that standardized inconsistent labeling for C-suite stakeholders, cutting a process from >2 weeks to <30 minutes through demos and business-focused communication.

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YL

Yutao Liu

Screened

Senior Software Engineer specializing in backend services and full-stack web platforms

Palo Alto, CA8y exp
AmazonUC Irvine

Project lead who partners with PM and customers to gather requirements, adjust project plans, and deliver new functionality that drives customer satisfaction and revenue. Has experience building features end-to-end and presenting successful technical demos to engineering and management audiences; no stated experience with LLM/agentic systems.

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JS

Justin Steele

Screened

Senior Strategy Consultant specializing in M&A due diligence and tax advisory

New York, NY14y exp
OC&C Strategy ConsultantsColumbia University

Consulting/workstream lead with private-markets due diligence experience (hedge fund client) spanning brand performance analysis and expert interviews across beverage categories. Also built and rolled out a UiPath RPA solution at KPMG to automate large-scale invoice review for tax recovery work, delivering ~30% efficiency gains and improving engagement realization.

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SC

Mid-level AI/ML Engineer specializing in Generative AI, LLM alignment, and RAG

CA6y exp
Scale AIUniversity of Texas at Arlington

Built and productionized a real-time enterprise RAG pipeline to improve factual accuracy and reduce LLM hallucinations by grounding responses in constantly changing internal knowledge bases (policies, manuals, FAQs). Experienced in orchestrating end-to-end ML workflows (Airflow/Kubernetes), handling messy multi-format data with schema enforcement (Pydantic/Hydra), and maintaining freshness via streaming incremental embeddings plus batch refresh. Also delivers applied ML solutions with non-technical teams (marketing/CRM) for segmentation and personalized engagement.

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KR

Executive Engineering Leader specializing in cloud services, distributed systems, and networking

Cupertino, CA29y exp
AmazonUniversity Visvesvaraya College of Engineering

Amazon engineering leader (15+ years) targeting Senior Manager/Director roles, with deep ownership of contact-center latency and reliability initiatives. Shipped a global production improvement cutting call latency 30–40% and led a complex Citrix SDK integration, including incident response and a backward-compatible rollout strategy to protect existing customers while enabling new features.

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DJ

Daming Jiang

Screened

Intern Software/AI Engineer specializing in LLM fine-tuning and agentic RAG systems

0y exp
AT&TCornell University

Built and shipped an end-to-end LLM agent during an AT&T internship to automate network troubleshooting, with production-style reliability safeguards (timeouts/retries/fallbacks) and structured, state-machine orchestration; project won 3rd place in AT&T’s nationwide intern innovation challenge and was demoed to leadership. Also handled messy multi-partner data at Tencent by implementing schema validation/normalization, confidence-threshold fallbacks, and idempotent Python/ORM-based pipelines.

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Priyanka Kaswan - Senior AI Research Engineer specializing in LLM agents and large-scale ML

Senior AI Research Engineer specializing in LLM agents and large-scale ML

7y exp
AT&TPrinceton University

AT&T Labs builder who deployed a production multi-agent LLM system that lets engineers ask natural-language questions and automatically generates deterministic, schema-grounded Snowflake SQL (200–400 lines) to detect anomalies in massive wireless/network event data (~11B events/day). Experienced with LangChain and Palantir Foundry orchestration, RAG-based result interpretation, and rigorous evaluation/monitoring loops to continuously improve reliability.

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AL

Aurel Lazar

Screened

Principal Software Engineer specializing in Unity game development and developer tooling

Renton, WA15y exp
Rec RoomGeorgia Tech

Unity/C# gameplay engineer from Rec Room who owned end-to-end systems spanning downloadable avatar content delivery (Addressables + auth/CDN), build automation/CI for asset bundles, and creator tooling (Avatar Studio). Also implemented AI-driven localization and generative mesh features, and has deep multiplayer experience with Photon and Photon Quantum across VR (Meta Quest) and mobile platforms, citing a 20% retention lift from faster content delivery and customization.

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KS

Junior Software Engineer specializing in distributed systems and machine learning

Sunnyvale, CA2y exp
GoogleUSC

Google backend engineer with strong experience in large-scale identity, membership, and access-control systems. Notable work includes reconciling customer IDs across 2B+ roster records and leading a 0-to-1 Drive sharing feature to classify external users as crossover members, with a strong emphasis on correctness, rollout safety, and low-latency service design.

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CY

Staff Software Engineer specializing in distributed systems and platform architecture

Aldie, VA15y exp
ProviUniversity of Maryland, College Park

Built a production LLM-powered data ingestion workflow at Provi, an online alcohol marketplace, to clean and match millions of distributor inventory items against a product catalog. Their experience is strongest in applying LLMs to real-world, large-scale data operations with AWS Glue, S3, batching, API integration, human review, and drift detection.

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LC

Lewis Chen

Screened

Mid-Level Software Engineer specializing in cloud infrastructure and data systems

Sunnyvale, CA4y exp
GoogleUC Berkeley

Backend engineer who helped redesign and refactor Forma’s backend during an app rewrite, emphasizing modularity, maintainability, and A/B testing support while delivering feature parity on a quarter-long timeline. Led a careful database migration using parallel databases with schema differences, validating integrity via staging and SQL checks, and has experience debugging subtle computer-vision overflow edge cases.

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TB

Thomas Baker

Screened

Senior Full-Stack Engineer specializing in serverless AWS and event-driven systems

Dallas, TX12y exp
AmazonUniversity of Texas at Austin

Backend/data engineer with experience at AWS and Intuit building and operating production serverless systems and data pipelines. Delivered an internal AWS TV video-processing platform using Step Functions/Lambda/S3/DynamoDB with strong reliability and cost controls, and built Glue-based ETL for compliance/risk events (Kafka to partitioned Parquet). Also modernized legacy compliance systems into Java/Node event-driven services and has demonstrated measurable SQL tuning impact (200s to 20s).

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ML

Executive Engineering Leader & Platform Architect specializing in Kubernetes PaaS and cloud security

Santa Monica, CA7y exp
StreamWalletsCarnegie Mellon University

Engineering leader who built and scaled a distributed team (Serbia + US) to deliver an internal multi-tenant Kubernetes-based PaaS, moving a large org from manual ops-driven deployments to automated CI/CD with >99.97% uptime and 100% service adoption. Known for culture change (blameless post-mortems, clear intake via ticketing) and security-first platform practices (tenant isolation, Falco) supporting SOC2 compliance; also operates at exec level with stakeholder communication and fundraising.

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CH

Chengzhu He

Screened

Staff/Principal Cloud Infrastructure Engineer specializing in Kubernetes and OpenStack

14y exp
TikTokShanghai University

Platform/backend engineer focused on Kubernetes at scale: built a Java control-plane service for multi-region cluster provisioning/monitoring/upgrades using Kafka-driven async workers, and solved peak-load provisioning failures by eliminating blocking I/O and dynamically scaling consumers. Also shipped an LLM-assisted Kubernetes troubleshooting/remediation feature that pulls Prometheus logs/metrics into prompts and uses guardrails (confidence thresholds + human-in-the-loop) to prevent risky actions.

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Nishant Pathak - Executive Engineering Leader specializing in cloud-native platforms and security

Executive Engineering Leader specializing in cloud-native platforms and security

14y exp
Kursaha TechnologiesIIT (BHU) Varanasi

Former CTO of EzCred, a fintech embedded finance/digital lending infrastructure startup that built an API-first underwriting and servicing platform using alternative data (e.g., GST and bank statements) to cut loan decisions from days to minutes. Helped raise $1M in seed funding, built the engineering org and compliance-ready cloud architecture, and ran partner pilots before the company shut down during COVID-driven lending market contraction.

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Jingfei Xu - Intern/Junior Software Engineer specializing in AI/ML and cloud-based systems in Mountain View, CA

Jingfei Xu

Screened

Intern/Junior Software Engineer specializing in AI/ML and cloud-based systems

Mountain View, CA0y exp
AmazonCarnegie Mellon University

Embedded/robotics software engineer with Hyundai Motors experience who owned an AI-driven perception validation pipeline using a Transformer-based approach to generate stable synthetic in-cabin audio for autonomy/ASR testing, cutting downstream testing time by 50%+. Has hands-on ROS integration (IMU sensor streaming, inference, control nodes), MQTT-based distributed messaging, and cloud/container deployment experience (Docker, Node/Express, AWS, CI/CD).

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