Vetted Java Professionals

“Backend-focused Python engineer who built an end-to-end personalized chatbot service integrating Amazon Redshift context retrieval with Amazon Bedrock, including prompt construction and production-grade reliability controls. Strong platform experience deploying containerized services to Kubernetes with GitOps/ArgoCD, plus hands-on Kafka streaming and phased infrastructure migration execution.”

“Backend engineer with experience building microservice-based systems that integrate LLM workflows (code review suggestions, documentation generation, test scaffolding) using REST APIs, Celery/Redis, and OpenTelemetry for observability. Demonstrates hands-on database and performance optimization in PostgreSQL/SQLAlchemy (bulk inserts, lock mitigation, cursor-based pagination) plus multi-tenant data isolation via tenant-aware models, middleware scoping, and schema/row-level strategies.”

“Robotics-focused Python developer who built autonomous navigation for a differential-drive robot using onboard vision and AprilTag detection, including pose estimation and coordinate frame transformations for localization and motion planning. Also has practical backend performance experience using Redis TTL caching to speed responses and reduce server load, plus basic PostgreSQL query/index optimization.”

“Search/backend engineer with hands-on experience improving Apache Solr-based search systems end-to-end (indexing strategy changes, ETL updates, and Java/Spring Boot Search API work). Demonstrated production rigor with QA partnership, A/B testing, and rollback-safe kill switches, plus measurable product impact (e.g., +1.5% add-to-cart) and operational troubleshooting including traffic/security mitigation.”

“AI/ML practitioner who built an Indian Sign Language recognition system (MediaPipe hand keypoints + CNN/RNN) as an accessibility-focused teaching aid, iterating closely with advocacy groups and educators and reaching 92% accuracy. Also has production-scale data migration experience at Saasgenie, using Kubernetes pod parallelization to migrate 1M+ ITSM records with a 5x throughput gain under API rate limits.”

“Full stack engineer in the financial/thematic investing domain who built end-to-end applications on AWS. Notably redesigned a slow portfolio analytics workflow by offloading heavy computations to scheduled AWS Lambda jobs and caching results in DynamoDB (TTL), cutting API latency from ~5 seconds to under 300ms while supporting data-heavy daily market processing.”

“Backend-heavy full-stack engineer with experience at Intuit (TurboTax Live) and Paytm payments, building and scaling Java/Spring Boot microservices for high-traffic transaction systems. Has hands-on wins improving peak-load performance using Redis/disk caching and Kafka event-driven patterns, plus React/Redux work for web app integration and strong monitoring practices with ELK.”

“Engineering leader with experience defining solutions from business requirements through detailed specifications and implementation, emphasizing cost-aware technology selection. Has led architectural changes including adding IBM Cloud alongside AWS for budget reasons and integrating caching/messaging to improve availability and performance, and describes scaling distributed teams via experienced DevOps/QA hires and structured evaluation.”

“Built a production-style PyTorch LSTM system that generates structured piano compositions from 1200+ MIDI files, then significantly improved long-range musical coherence by implementing Bahdanau attention based on research literature. Also has internship experience using Docker Compose for containerized backend workloads and has independently used Ray to scale ML experiments across multiple GPUs, including dealing with GPU scheduling/memory oversubscription issues.”

“Enterprise Architecture leader with insurance domain experience (Farmers Insurance) who drove a multi-phase roadmap to modernize a siloed CRM landscape—migrating from legacy Siebel to Salesforce Financial Services Cloud with Customer 360, MDM, and omnichannel capabilities. Also led a high-impact architecture decision to implement offline billing to reduce customer-facing downtime, including complex SAP/on-prem-to-cloud integration and transaction sync.”

“Customer support professional with Scrum Master and Product Owner certifications who has handled high-stakes account security incidents (including locking down an account to protect over $200k) and troubleshot live data feed integrations (XML/socket) by identifying IP whitelisting mismatches. Emphasizes transparent stakeholder communication, escalation, and building internal wiki documentation to prevent repeat issues.”

“Backend/AI workflow engineer at a startup building production AI services for fashion workflows, including an AI-powered techpack generation API in Go (Gin) with MongoDB handling ~1k+ daily requests. Recently implementing an image-to-3D dress generation feature end-to-end, integrating a Python FastAPI AI service with ComfyUI + Hunyuan, with strong emphasis on async orchestration, webhooks, and observability (OpenTelemetry + SigNoz).”

“Fintech product engineer working on a large-scale credit monitoring platform (tens of millions of users) with deep experience in regulated banking integrations, PII security, and step-up/MFA flows. Has shipped customer-facing React/TypeScript experiences driven by Optimizely experimentation and built reliable partner-facing microservices/SDKs on AWS, including resolving production traffic loss caused by edge security (DataDome/CAPTCHA) conflicts with payment providers.”

“Full-stack engineer who built and owned an AI-assisted job-matching dashboard in Next.js App Router/TypeScript, keeping LLM logic server-side and improving performance via deduplication, caching/revalidation, and streaming (35% fewer duplicate LLM calls; 40% faster first render). Also has strong data/backend chops: designed Postgres models and optimized queries at million-record scale (1.8s to 120ms) and built durable AWS multi-region telemetry workflows with idempotency, retries, and monitoring.”

“Software engineer with experience at Striim and Amazon who ships end-to-end production systems across UI, backend, ML, and operations. Built a real-time PII detection capability for a streaming data platform by integrating Python ML inference into a Java monolith via gRPC sidecars, achieving ~3M events/hour throughput and ~93% accuracy, and helped drive enterprise adoption (Fiserv, CVS). Also modernized internal Amazon tooling for multi-region scale with modularization and fully automated deployments.”

“Backend/platform engineer with payroll domain depth who built high-volume payroll processing microservices (Java/Spring Boot, Kafka, PostgreSQL, Redis) on AWS Kubernetes and debugged major peak-cycle latency by redesigning transaction boundaries and moving to async Kafka processing (>50% latency reduction). Also shipped an LLM-powered HR assistant using RAG with strong security/guardrails (RBAC, PII masking, audit logs) that cut support tickets by 40%, and designed reliable multi-step agent workflows with retries, circuit breakers, and idempotency.”

“Backend/AI workflow engineer with PayPal experience building workflow-driven financial compliance systems (Python/Java, Postgres, AWS/EKS) at thousands of executions/day. Has shipped production LLM-powered document extraction with strict schema/rule validation, auditability, and human-in-the-loop fallbacks, and has deep expertise in reliability (idempotency, locking, state machines) and Postgres performance tuning.”

“QA automation engineer with healthcare web experience who owned an end-to-end automated test suite (Java/Cucumber/Selenium and Cypress) and integrated it into CI/CD (Jenkins to GitHub Actions, qTest DoD gates). Known for boosting regression coverage to ~93%, stabilizing flaky Cypress tests, and catching production-impacting pipeline/environment redirect issues through workflow updates and cross-browser/regional scenario testing.”

“Full-stack engineer at Bank of America who built and iterated a real-time transaction monitoring/fraud detection system processing 50K+ daily transactions, improving latency (25%), dashboard performance (30%), and reducing manual investigation time (40%) while meeting PCI DSS via OAuth2 and RBAC. Also built a scalable ETL pipeline for messy financial data with strong reliability/observability (ELK, retries, DLQ), boosting data integrity from 87% to 99% and sustaining 99.8% uptime.”

“Application-focused software engineer with experience at Amazon and Motorola shipping production systems ranging from developer monitoring/on-call tooling (Alcazar, ~40% MTTR improvement) to consumer AI features used by 100K+ users. Currently building an AI/ML-driven platform with a Python/FastAPI backend on AWS (ECS/RDS/S3) and has handled real production latency/scaling incidents end-to-end.”

“Backend/LLM engineer who built a production-critical Amazon Bedrock + RAG correction and compliance layer for employee communications, integrating tightly with existing Spring Boot/AWS microservices to reduce manual review while keeping outputs explainable and auditable. Also designed an event-driven system processing 10M+ events/day (SQS/Lambda/DynamoDB/Elasticsearch) and handled on-call incidents with strong observability and reliability patterns (idempotency, retries, hotspot mitigation).”

“Software engineer intern at Nutanix who independently shipped and maintained an internal smoke-test/failure-analysis dashboard, integrating failure data from multiple upstream systems (e.g., Jira, Jenkins, CircleCI) via REST APIs. Also has prior data-science experience building Postgres-based asset management analytics with automated reporting and indexing for faster time-series retrieval.”

“Backend/data engineer focused on compliance and statistical processing systems on AWS, building containerized FastAPI services plus event-driven async workflows (Step Functions/EventBridge) with strong reliability patterns (JWT auth, idempotency, structured logging). Has modernized SAS-based batch pipelines into modular Python/AWS services with parallel-run parity validation, and has demonstrated measurable SQL performance wins (40+ min to <10 min) and hands-on incident ownership using CloudWatch-driven detection and prevention.”

“Gameplay/AI engineer with end-to-end ownership of racing-sim AI (fair physics parity, competitive overtaking) and strong iteration tooling (live tuning + config). Has shipped networked VR multiplayer work at Ready At Dawn, including a consensus-style goal validation approach to reconcile non-deterministic replication/smoothing discrepancies, plus experience with Havok/Bullet, spline math (Catmull-Rom), and complex creature/boss animation behaviors.”