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Vetted Java Professionals

Pre-screened and vetted.

JavaPythonDockerJavaScriptCI/CDAWS
KR

Kaustubh Rai

Screened

Junior Software Engineer specializing in scalable distributed systems and cloud platforms

Pittsburgh, PA2y exp
eParts Services LLCCarnegie Mellon University

“Backend engineer with experience at UnitedHealth Group redesigning a high-traffic Spring Boot microservice from blocking to reactive architecture during peak season, cutting median latency by 47% for a service used by ~10M customers annually. Strong in Kubernetes-based deployment/scaling and pragmatic rollout strategies (blue-green/incremental traffic shifting) with performance and database troubleshooting.”

.NETApache HadoopApache KafkaAWSAWS LambdaAzure Data Factory+70
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DS

Darsh Sharma

Screened

Mid-level Software Engineer specializing in ML systems and microservices

Madison, WI2y exp
TeradataUniversity of Wisconsin–Madison

“Teradata Text Security intern who built a production LLM-powered planner agent that decomposes complex tasks into dependency-aware subtasks (DAG/topological graph) and executes them via a custom orchestrator with parallelism, status tracking, and error handling. Also contributed to an HR-facing internal document chatbot concept to streamline onboarding, showing cross-functional collaboration.”

CC++CUDAPythonJavaSQL+101
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RZ

Robert Zhu

Screened

Mid-level Robotics & Systems Engineer specializing in GPU virtualization and autonomous manipulation

Toronto, Canada3y exp
AMDNorthwestern University

“Robotics software engineer focused on vision-guided manipulation with a Franka Emika Panda on ROS 2, using an RGB-D camera and a trained YOLO-OBB detector to estimate 3D object poses for pick-and-place. Strong in perception-to-planning integration (TF2 alignment, message synchronization, MoveIt 2) and in debugging sim-to-real issues, including symmetry-aware orientation handling and grasp repeatability tuning.”

BashCC++Computer VisionDockerGazebo+75
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SB

Sowmya Battu

Screened

Mid-level Full-Stack Software Engineer specializing in cloud-native platforms

Greater Seattle Area, WA6y exp
AmazonUniversity of Houston

“Amazon experience integrating LLM-powered chat automation into Amazon Connect contact-center workflows, taking prototypes to production with compliance-minded guardrails, schema/policy validation, and robust fallbacks. Regularly supports rollout and adoption via developer workshops, integration guides, and customer calls, with strong production triage and observability practices.”

JavaKotlinPythonTypeScriptJavaScriptSQL+89
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SG

Sarthak Gupta

Screened

Mid-level AI/ML Engineer specializing in LLMs, NLP, and real-time AI systems

New York, NY4y exp
New York UniversityNYU

“Backend engineer who built a real-time pipeline for recording, transcribing, and analyzing audio from 400+ news radio stations, scaling Whisper on an HPC cluster with 7 H100 GPUs. Has strong performance optimization experience (30% latency reduction via SQL/query design; 50% DB call reduction via Redis caching) and has implemented region-based data isolation and PII protections in a regulated environment (JP Morgan Chase).”

PythonPandasNumPySciPyJavaC+113
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PJ

Po Jui Lin

Screened

Mid-Level Full-Stack Engineer specializing in cloud platforms, cybersecurity web apps, and IoT

Seattle, WA3y exp
AmazonUniversity of Washington

“Backend engineer with experience at Amazon building an API-driven service (APS) for large-scale prompt optimization jobs using AWS Step Functions, Batch/Fargate, DynamoDB, and S3, emphasizing idempotency, observability, and secure execution boundaries. Also led a multi-tenant enterprise policy/configuration backend refactor at MAMIT Cyber with versioned schemas, shadow writes, feature-flagged rollout, and PostgreSQL RLS-based tenant isolation.”

PythonJavaScriptTypeScriptC++JavaVue.js+92
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SL

Sri Lekha Kandadai

Screened

Mid-level Machine Learning Engineer specializing in MLOps and multimodal AI

KS, USA5y exp
AppleUniversity of Central Missouri

“ML/AI engineer focused on production-grade model reliability: built a monitoring and validation framework to detect drift, trigger anomaly alerts/retraining, and maintain consistent performance for device intelligence workflows at scale. Strong MLOps background with Python pipelines, Docker/Kubernetes deployments, Airflow orchestration, and real-time monitoring dashboards; experienced partnering with product managers to deliver business-facing insights.”

PythonSQLRC++JavaMachine Learning+80
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RB

Rojin Bakhti

Screened

Junior Software Engineer specializing in Edge AI and ML deployment

San Diego, CA3y exp
QualcommUSC

“Qualcomm engineer building Android applications that run on Qualcomm AI accelerators, with hands-on experience in C++ concurrency, chipset stress testing, and power/performance tuning. Has deployed on-device AI models and built deployment/log post-processing workflows using Docker/Kubernetes and CI/CD; interested in translating this embedded AI/performance background into robotics (perception/real-time systems).”

AndroidAWSCC++CI/CDC#+74
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JG

Jayanth Godi

Screened

Mid-level Site Reliability Engineer specializing in cloud infrastructure, Kubernetes, and LLM applications

San Jose, CA6y exp
AmazonSan Jose State University

“SRE-focused engineer with experience at Sony Interactive Entertainment productionizing high-throughput LLM/agentic systems on Kubernetes, including GPU-aware autoscaling and warm-pool strategies to manage latency and cost under traffic spikes. Demonstrates strong incident response using Prometheus/Grafana + Jaeger tracing (e.g., resolving recursive agent loops and restoring 99.9% availability within minutes) and partners closely with sales/customer teams through PoV demos and developer workshops.”

AWSMicrosoft AzureDockerKubernetesLinuxPrometheus+86
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SS

Shubham Singh

Screened

Mid-level Software Engineer specializing in LLM systems and intelligent search

CO, USA6y exp
PalantirSan José State University

“Backend engineer from Palantir who built and productionized an enterprise LLM-based document intelligence/search platform, evolving it into a hybrid lexical+vector retrieval system. Emphasizes reliability and cost control via strict LLM gating, robust fallback paths, and evaluation frameworks (e.g., MMLU/BLEU), plus disciplined migration practices (feature flags, dual-writes, shadow reads) to ship changes safely at scale.”

AJAXAPI DesignAPI GatewayApache KafkaApache TomcatAgile+181
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SA

Suhas Athreya

Screened

Junior Salesforce & AI Product Consultant specializing in public sector and enterprise platforms

Bengaluru, India2y exp
Overleap NetworksCarnegie Mellon University

“Software/cloud engineer with PwC experience deploying a nationwide Australian Government Salesforce labor licensing platform used by 200k+ professionals, emphasizing safe integration, CI/CD, and UAT-driven quality improvements (40% defect reduction). Also built a Python/FastAPI RAG system with the U.S. Army to convert CONOP documents into risk assessments, adding human-in-the-loop and provenance features to address operator trust concerns.”

PythonSQLJavaJavaScriptREST APIsLangChain+95
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PP

Pranav Puranik

Screened

Senior AI Engineer specializing in LLMs, RAG, and multimodal NLP

Austin, TX5y exp
Health Care Service CorporationUniversity of Florida

“Built a production LLM/RAG assistant for insurance/health claims agents that ingests 100–200 page patient PDFs via OCR (migrated from local Tesseract to Azure Document Intelligence) and delivers grounded claim detail retrieval plus summaries with PII/PHI guardrails. Experienced orchestrating large workflows with Celery worker pipelines and AWS Step Functions (S3-triggered, Fargate-based batch inference/accuracy aggregation), and collaborates closely with non-technical SMEs (claims agents/nurses) through shadowing, iterative demos, and SME-defined evaluation.”

PythonSQLJavaTypeScriptBashUnix+120
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SS

Shubham Singh

Screened

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

Pittsburgh, PA6y exp
Musing AICarnegie Mellon University

“Built and shipped a production multi-agent, voice-based conversational assistant for older adults’ daily health management using Vertex AI, FastAPI, Firebase/Firestore, and Cloud Run, with a custom cross-session memory design to keep responses context-aware at low latency. Also partnered with caregivers/elderly users and health officials, translating needs into workflows and explaining HIV risk predictions with SHAP and dashboards.”

BigQueryCI/CDCC++Computer VisionContainerization+108
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JY

Jiacheng Yin

Screened

Intern Software Engineer specializing in data engineering and AI agent systems

Beijing, China1y exp
JD.comCornell University

“AI engineer at Anote.ai who built and shipped a production multi-agent LangGraph/LangChain/Ray RAG platform for enterprise search and workflow automation, supporting 3 commercial products and 100+ developers. Drove measurable gains (30% accuracy improvement, lower latency) and improved reliability with Redis-based state checkpointing, message-queue synchronization, and Milvus retrieval optimizations, while partnering with PMs/clients to add transparency features like confidence scores and real-time logs.”

.NETAgileAmazon CloudFrontAngularAnomaly detectionAPI Gateway+158
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MS

Manjory saran

Screened

Senior Backend & Infrastructure Engineer specializing in cloud-native distributed systems

5y exp
WalmartSan José State University

“LLM infrastructure engineer who built a production-critical real-time personalization and memory retrieval system for a user-facing product, adding <100ms P99 latency while improving relevance ~20–25% and holding SLA through 3x traffic. Experienced designing tiered retrieval backends (Redis + vector store), deploying on Kubernetes with autoscaling/circuit breakers, and running rigorous observability, incident response, and agent evaluation (shadow traffic, A/B tests, regression/replay).”

API DesignAsynchronous ProcessingAWSAWS CloudFormationCachingCI/CD+105
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FA

Feras Alsaiari

Screened

Senior Software Engineer specializing in AWS data platforms and event-driven systems

4y exp
Capital OneGeorgia Tech

“Capital One engineer leading the architecture and delivery of a large-scale AWS Glue/Spark/Delta Lake batch messaging pipeline that decoupled batch from real-time flows, added multi-region failover and automated retries, and delivered ~40% AWS cost savings with ~3x performance gains. Currently building an LLM-powered Slack bot using RAG to automate message investigations by querying CloudWatch, Snowflake, and internal documentation with privacy-aware masking of NPI/PII.”

PythonJavaJavaScriptSQLCC+++91
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CL

Changhee Lee

Screened

Mid-level Software Engineer and Product Manager specializing in AI and financial data platforms

Remote4y exp
AI MelodyCornell University

“Full-stack engineer with deep Next.js App Router + TypeScript experience who has shipped and owned production features in a fashion/wardrobe/resale domain. Demonstrated measurable impact across the stack: +25% engagement, 30% faster load times, 40% fewer errors, plus durable Temporal workflows and Postgres analytics/query tuning for real-time dashboards.”

PythonJavaGitSQLJiraConfluence+64
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TD

Tom Dinwiddie

Screened

Executive IT Leader specializing in global SaaS, cloud transformation, and M&A integration

20y exp
AutoZoneUC Irvine

“Technology executive/CTO-type leader with experience at ALLDATA defining and operationalizing an executive-prioritized roadmap, scaling distributed engineering teams (including expansion in Mexico and India), and modernizing products onto a containerized Google Cloud architecture. Highlights include 99.96% reliability, 38% maintenance cost reduction, and strong security/compliance posture (CyberArk, ISO27001, SOC2, SOX).”

AlgorithmsArtificial IntelligenceCI/CDCloud ComputingData PipelinesDevOps+132
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TJ

Travis Johnson

Screened

Senior Full-Stack Software Engineer specializing in FinTech payments and fraud systems

Plano, TX8y exp
AffirmTexas Tech University

“Backend/data engineer with production experience building credit/fraud enrichment services and checkout pipelines on AWS (EKS + Lambda) using FastAPI, Kafka, Postgres, and Redis, with a strong focus on reliability patterns (timeouts/retries/circuit breakers) and observability. Has also built AWS Glue/PySpark ETL into S3/Redshift with schema evolution and data quality controls, and modernized legacy credit decisioning into Java/Node microservices with parallel-run parity validation and feature-flag rollouts.”

JavaJavaScriptTypeScriptPythonSQLAWS+98
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SV

sasanka voleti

Screened

Senior DevOps & Site Reliability Engineer specializing in cloud reliability and observability

9y exp
Goldman SachsCalifornia State University, East Bay

“Built and deployed a production AI/ML SRE copilot that uses RAG over real-time Splunk signals plus deployment/runbook data to generate grounded incident summaries and next steps, cutting time-to-contact by 30%. Treats the knowledge corpus like a production dataset (quality gates, semantic chunking, metadata enrichment) and runs golden-dataset automated evals to ensure reliability, while partnering closely with ops/support leaders through discovery sessions and metric-driven demos.”

Site Reliability EngineeringCI/CDJenkinsGradleCloud ComputingAWS+79
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CM

Chetan Mukhopadhyay

Screened

Senior Engineering Manager specializing in software quality, automation, and web/mobile platforms

Seattle, WA16y exp
BayerCal State Long Beach

“Engineering leader at Bayer Crop Science leading a Core Platform team responsible for widely used open-source TypeScript/React and mobile SDKs (npm/GitHub) embedded across 10M+ monthly active devices. Known for shipping high-performance, backward-compatible developer frameworks with rigorous release discipline (bi-weekly releases, 99.99% uptime, long streaks of zero breaking changes) and major DX wins (onboarding cut to minutes, support tickets down 82%).”

AgileAPI TestingAWSCC#C+++141
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SP

Siyuan Peng

Screened

Engineering Manager specializing in enterprise SaaS, cloud analytics, and ML-driven systems

Atlanta, GA11y exp
Keysight TechnologiesGeorgia Tech

“Engineering leader who managed a 20-person cross-functional team building customer-driven software solutions, delivering a 50% reduction in simulation/test lifecycle and securing a long-term strategic SLA. Strong in scalable data ingestion architectures (FastAPI + Kafka + multiprocess workers), operational diagnostics (correlation IDs/centralized logging), and microservice decoupling for analytics/visualization. Active open-source contributor who shipped a NATS bug fix and improved SDK onboarding with automation that cut ramp time by 30%.”

AJAXAngularAWSBootstrapC#CI/CD+93
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CM

Chaitanya Mahajan

Screened

Intern/Junior Software Engineer specializing in ML, networking telemetry, and full-stack web apps

Louisville, CO1y exp
CableLabsUniversity of Colorado Boulder

“Backend-focused engineer with hands-on experience modernizing a legacy SNMP/PNM data collection system at CableLabs into a cloud-accessible Kubernetes pipeline, feeding Prometheus-formatted metrics into VictoriaMetrics and visualizing real-time network health in Grafana for 100+ modems. Also built a FastAPI + Supabase appointment booking portal for a clinic with encryption and phone-number-based auth, and has frontend experience debugging S3-based HEIF image rendering issues.”

PythonCC++JavaHTMLCSS+103
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NB

Neha Baadadmath

Screened

Executive Software Engineering Leader specializing in Trading, Payments, and FinTech platforms

Phoenix, AZ18y exp
LPL FinancialVisvesvaraya Technological University

“Entrepreneurially minded operator with experience in trading-platform environments who prototyped a vector-database layer to generate contextual incident narratives and reduce MTTR/escalations. Also building a non-tech venture: luxury wine distribution into India and broader Asian markets, sourcing directly from wineries with a Master of Wine and planning tier-1 launch via restaurant-owner connections while navigating complex import duties and licensing.”

Strategic PlanningProject ManagementProgram ManagementStakeholder ManagementVendor ManagementScrum+113
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