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Vetted Java Professionals

Pre-screened and vetted.

MA

Senior DevOps/Site Reliability Engineer specializing in multi-cloud Kubernetes platforms

Austin, TX11y exp
KIBO
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PM

Mid-level Data Scientist specializing in ML, NLP, and LLM-powered analytics

Westlake, OH4y exp
KeyBank
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VC

Senior QA Analyst specializing in test automation, API testing, and ETL/data validation

9y exp
UPS
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DP

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

Columbus, IN6y exp
Cummins
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JP

Senior Software Quality Assurance Engineer specializing in automation, CI/CD, and release quality

Los Angeles, CA12y exp
IMAX
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AD

Mid-Level Full-Stack Software Engineer specializing in cloud and kiosk applications

Chicago, IL6y exp
The Aspen Group
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DD

Engineering Leader specializing in FinTech, payments, and enterprise platforms

23y exp
QRails
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RD

Senior QA Engineer specializing in test automation, API validation, and CI/CD quality

St. Louis, MO9y exp
KnowInk
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KS

Senior Full-Stack Java Engineer specializing in cloud microservices and FinTech/insurance platforms

Chicago, IL6y exp
State Farm
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AB

Mid-Level Full-Stack Java Developer specializing in Spring Boot microservices and Angular

Riverwoods, IL7y exp
Discover
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KS

Senior SDET specializing in mobile, telecom, and test automation

Irvine, CA9y exp
Take2 Consulting
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KA

Mid-level Backend Software Engineer specializing in Java, Spring Boot, and AWS

Dallas, TX5y exp
Paycom
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TG

Tushar Gwal

Screened ReferencesStrong rec.

Mid-level AI/ML Engineer specializing in GenAI, computer vision, and MLOps

Tallahassee, FL4y exp
Product Manager AcceleratorIllinois Institute of Technology

AI engineer with experience taking a GPT-4-powered GenAI career coach toward production on Azure AI Foundry, re-architecting the backend with hybrid (vector + keyword) search and RAG optimizations to cut latency by 50%. Also has client-facing TCS experience building healthcare ETL pipelines and delivering error-free monthly reports, plus current work analyzing agentic system reasoning traces and guardrail drift as an AI research fellow.

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BR

Bharath Reddy Nallu

Screened ReferencesStrong rec.

Mid-level Machine Learning Engineer specializing in NLP and scalable MLOps

4y exp
Northern TrustUniversity of the Cumberlands

Data/ML engineer in financial services (Northern Trust) who built a production RAG-based LLM system to connect structured transaction/portfolio data with unstructured market and internal documents for risk teams. Strong in end-to-end pipelines (AWS Glue/Airflow/PySpark), entity resolution, and taking models from prototype to reliable daily production with performance tuning (LoRA + TensorRT) and monitoring.

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AK

Ashutosh Khatavkar

Screened ReferencesStrong rec.

Mid-level SDET/Software Engineer specializing in test automation and CI/CD

Syracuse, NY3y exp
UbisoftSyracuse University

AAA game QA professional from Ubisoft (For Honor) with deep live-service multiplayer experience. Known for owning network/competitive integrity risks and building a custom network simulation tool to reliably reproduce desync issues, accelerating debugging and saving 100+ hours. Strong end-to-end QA process skills spanning test planning, triage, regression, and release verification using JIRA/TestRail.

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IP

Igor Prizzi

Screened ReferencesStrong rec.

Senior Game Programmer specializing in Unity gameplay systems and animation tech

London, United Kingdom19y exp
Outright GamesUniversity of Catania

Unity developer with cross-platform shipping experience (console and mobile) who optimized an open-world game to run on Nintendo Switch at 30 FPS by building a dynamic character pooling/occlusion-culling management system that created the illusion of hundreds of NPCs with only ~30 active. Has owned core character systems (player/NPCs, customization, interactions) and also applies AI tools to rapidly iterate on personal projects like a profitable trading bot strategy.

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BI

Bhavesh Ittadwar

Screened ReferencesStrong rec.

Senior Full-Stack Engineer specializing in scalable web and cloud systems

USA3y exp
Heartland Community NetworkNorth Carolina State University

JavaScript engineer who built a Michelin-specific headless CMS forms platform based on apostrophe-forms, powering forms across 400+ Michelin websites. Designed an extensible, SOLID-aligned modular field architecture with a shared design system, cutting hundreds of lines of per-project code across 10+ implementations while driving cross-device compatibility and performance (BrowserStack, Lighthouse, SSR).

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SM

Sai Manikanta Kasireddy

Screened ReferencesStrong rec.

Mid-level Machine Learning Engineer specializing in cloud-native GenAI and RAG systems

5y exp
Revstar ConsultingUniversity of North Texas

Built and productionized an internal GenAI chatbot that makes company policy/SOP knowledge instantly searchable, using a secure RAG architecture on AWS (Bedrock/Titan embeddings/OpenSearch Serverless, Textract/Lambda/S3 ingestion, Claude 3 Sonnet). Demonstrates strong MLOps/orchestration experience (Airflow, Step Functions with Lambda/Glue/SageMaker) and a rigorous reliability approach (RAGAS metrics, A/B testing, citation validation, monitoring), including collaboration with compliance stakeholders via review dashboards.

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PK

Praniket Ketan Walavalkar

Screened ReferencesStrong rec.

Junior AI Software Engineer specializing in RAG agents and cloud data platforms

Seattle, WA1y exp
University of WashingtonUniversity of Washington

AI Software Engineer (student employee) at University of Washington IT who helped deploy "Purple," a governed, explainable LLM platform on Azure used by 100,000+ students/faculty/staff. Independently led scalable reliability efforts by building automated agent quality/load/red-team testing and CI/CD health validation (Playwright/Node.js, Azure DevOps), and previously built an explainable AI scheduling assistant for clinical operations at Proliance Surgeons.

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AK

Alifya Kitabi

Screened ReferencesStrong rec.

Senior QA Engineer specializing in SaaS payments and legal tech

San Diego, CA22y exp
8amNJIT

QA professional from fintech/SAP security and complex identity systems who has owned end-to-end testing across the SDLC, including being the sole QA on a high-risk payment platform carrier migration. Demonstrated strength in integration testing, data integrity validation, and diagnosing calculation/automation defects using controlled test data and scripted date emulation; experienced with JIRA/TestRail and Selenium-based regression coverage.

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NR

Nakul Reddy Sarasani

Screened ReferencesStrong rec.

Junior Full-Stack Software Engineer specializing in cloud-native distributed systems

Dallas, USA3y exp
JPMorgan ChaseUniversity of North Texas

Software engineer with JPMorgan Chase experience building a real-time operations console backend on Spring Boot/Kafka/Kubernetes and resolving peak-load latency through profiling, indexing, caching, and async processing. Also built and owned an AI-driven digital-archives metadata pipeline during a master’s at UNT using OCR + LLaMA-based prompting with validation, near-human accuracy, and human-in-the-loop guardrails.

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PD

Preetham Dandu

Screened ReferencesModerate rec.

Junior Software Engineer specializing in backend, distributed systems, and cloud platforms

Stony Brook, NY1y exp
Stony Brook UniversityStony Brook University

MS candidate with strong backend/data engineering focus who builds research and data systems with production-grade rigor (reproducibility, observability, restartability). Has hands-on experience securing and scaling FastAPI-based gateways in front of Java microservices, leading SQL Server→Snowflake migrations with dual-write/feature-flag rollouts, and hardening Kafka-based fleet-tracking systems against out-of-order and duplicate events.

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DC

Deepika Chudi

Screened

Mid-level Full-Stack Engineer specializing in React, TypeScript, and Spring Boot

Seattle, WA5y exp
CuraJoyNortheastern University

Full-stack engineer with strong Next.js App Router/TypeScript experience who built production dataset search/filtering and data-heavy dashboards backed by Postgres. Demonstrates hands-on performance work across the stack (EXPLAIN ANALYZE, composite indexes, caching, React profiling/memoization) and has built durable, Temporal-like orchestrated data-processing workflows with idempotency and retry strategies in an early-stage startup environment (Gaia AI).

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