Vetted Java Professionals

“Built a production AI-powered insights platform for marketing teams analyzing large-scale social and news data, combining Java microservices, Kafka, Spark, React, and LLM-based retrieval workflows. Stands out for shipping customer-facing AI features with measurable gains in accuracy and latency, plus solid reliability practices for high-volume backend systems.”

“Software engineer with experience building internal tools and admin consoles, including a stealth startup database management console and a Fidelity internship project that transformed QA test coverage tracking from unwieldy Excel sheets into a clearer, more actionable UI. Strongest signals are end-to-end ownership, modular app design, and practical iteration based on user feedback.”

Thomas Le

Screened

Junior Full-Stack Software Developer specializing in web, mobile, and health tech

Remote2y exp

“Developer who uses AI as a productivity accelerator while maintaining strong ownership of code quality, security, and readability. Built an AI-powered planning tool during the PolyPrompt hackathon that transformed messy project requirements into structured tasks, timelines, and assignments, and has also led human teams through Veggie Rescue with a focus on user-aligned execution.”

“Candidate takes a disciplined, developer-in-the-loop approach to AI-assisted coding, using AI primarily for brainstorming, suggestions, and optimization while retaining full ownership of architecture and final code decisions. They also actively stay current on AI developments through research papers, communities, and emerging tools.”

“State Street engineer who identifies operational pain points and turns them into high-impact internal platforms, including a service-health monitoring system and a Databricks log standardization pipeline used by 200+ users. Also experiments with practical LLM workflows, having built a Claude-based AI host that dramatically reduced facilitation time for a growing book club.”

“Backend engineer with end-to-end ownership experience on a real-time AI-driven payment authorization/orchestration platform at PayPal. They describe strong fintech systems depth across Java/Spring/Kafka microservices, database and latency optimization, and reliability engineering, with concrete impact including 35% fewer processing failures, latency reduced from 420ms to 140ms, 1,200+ weekly manual reviews eliminated, and 40% faster incident response.”

“Founding engineer who has built web products end-to-end in startup settings, spanning FastAPI/React application development, auth, cloud deployment, and Kubernetes-based scaling. Particularly notable for designing custom GPU autoscaling for an AI-style recommendation product and later shipping workflow-driven healthcare support tooling using Temporal, Postgres, and modular backend logic.”

“Candidate brings practical GenAI engineering experience with a disciplined approach to AI-assisted development. They have designed lightweight multi-agent workflows for a RAG-based support copilot, including retrieval, relevance validation, response generation, and groundedness checks to reduce hallucinations.”

“Early-career candidate with a thoughtful, engineering-first approach to AI-assisted development: they use AI to accelerate implementation while retaining human ownership of architecture and final code quality. They recently built a speech-to-text workflow using Groq Whisper and showed practical judgment by designing around imperfect transcription accuracy with checks and fallback handling.”

“Senior engineering leader with deep hands-on experience scaling and stabilizing complex SaaS platforms, including leading the OneLogin identity platform and managing globally distributed teams of up to 105 people. Particularly strong in reliability engineering, infrastructure modernization, and cross-functional execution, with a track record spanning platform unification, enterprise product delivery, and tailored Agile transformations.”

“LLM/agent engineer who shipped a two-stage AI recruitment screening platform at Foursquare that automated resume ingestion through behavioral assessment, delivering an 85% reduction in screening time across 5,000+ applications with auditability and confidence-gated decisions. Also built a multi-agent benchmarking framework using MCP tool interfaces and a RAGAS + LangSmith evaluation/observability stack, including async re-architecture that cut production latency by 50%.”

“Backend/platform engineer who has built and run production Python/Flask + Kafka microservices processing RFID and camera/RFID fusion streams for near-real-time retail cart updates at ~4–5M events/day. Strong in reliability/performance debugging (p99 latency, Kafka lag, Cosmos DB RU hot partitions) with measurable impact including ~30% database cost reduction, and has also shipped an end-to-end vulnerability scanning workflow with DynamoDB-backed state, idempotency, and robust retry/verification guardrails.”

“Robotics/software engineer who deployed a Raspberry Pi computer-vision-controlled 3-axis platform at FuelCell Energy, improving screen-print alignment from >10mm to 0.01mm repeatability via encoder-based closed-loop PID control. Currently designing an AI-enabled hearing-aid accessory for the cocktail party problem using a multi-mic array, beamforming, and an edge-accelerated neural network with <10ms latency via shared-memory DSP integration.”

“Full-stack engineer who built an LLM-powered productivity web app (LifeOS) end-to-end with TypeScript/Next.js, Prisma, and Postgres, emphasizing fast iteration with stable API contracts and an isolated AI service boundary. Also built a security/compliance login-verification workflow at Medpace used within an internal admin portal for thousands of employees, and has AWS experience orchestrating batch GPU workloads with robust retry/idempotency patterns.”

“Robotics software contributor with hands-on experience building a Gazebo/ROS(2) Mars rover simulation integrating LiDAR and image segmentation for autonomous navigation and SLAM (Nav2). Comfortable debugging low-level sim/model integration issues (URDF/XML) and building sensor-data pipelines, and has also shipped a real-world telemetry setup streaming vibration data over UDP with packet-loss mitigation.”

“Built and deployed a production LLM/RAG clinical decision support system that enables real-time semantic search over unstructured EHR notes and delivers patient risk insights. Strong in healthcare-grade MLOps and compliance (HIPAA, PHI handling, encryption, RBAC, audit logs) and scaled embedding/retrieval pipelines using Spark/Databricks and Airflow. Partnered with clinicians via Power BI dashboards and explainability, contributing to an 18% reduction in patient readmissions.”

“Capgemini engineer who helped take a travel insurance platform from prototype demos to a stable production system by clarifying requirements, hardening API contracts, and adding validation/logging to handle real customer data and external integrations. Experienced in real-time troubleshooting of complex workflows (including LLM/agentic-style workflows) through strong observability practices, and in leading practical developer-focused demos that accelerate client integration and adoption.”

“Built and deployed an enterprise GenAI knowledge assistant over thousands of internal PDFs/reports using a RAG stack (GPT-4 + Hugging Face embeddings + vector DB) to reduce manual search and SME escalations. Uses LangGraph/LangChain to orchestrate modular agent workflows with relevance filtering and fallback handling, and applies rigorous evaluation (golden datasets, edge cases, A/B tests) with production monitoring metrics.”

“AI/LLM engineer with production experience at Charles Schwab building a RAG-based assistant to help 5,000+ reps answer complex financial policy questions. Implemented a multi-layer anti-hallucination approach (GNN-driven ontology/graph retrieval + citation-only answers) and compliance-focused guardrails (Azure AI Content Safety) in partnership with audit/compliance stakeholders.”

“Interned at Zonda where he built an AI-driven semantic search solution over ~280M housing/builder records. Iterated from local LLMs via llama.cpp quantization to a vector-embedding retrieval system, then boosted semantic accuracy with a custom spaCy NER layer and re-ranking, optimizing for latency through precomputation. Collaborated with economics-focused stakeholders to reduce manual document/paperwork time by enabling natural-language search over internal data.”

“Engineer with banking and industrial/IoT experience who has deployed a payment-processing microservice with zero downtime, handling Protobuf schema evolution and sensitive data migration via dual-write/checksum techniques. Demonstrates strong cross-stack troubleshooting (pinpointed intermittent distributed timeouts to a failing ToR switch port) and customer-facing Python ETL customization using plugin-based parsers and Pydantic validation, plus hands-on monitoring/alerting improvements with operators.”

“Built and deployed a production LLM-powered internal documentation assistant using embeddings, a vector database, and a RAG pipeline to reduce time spent searching PDFs/manuals. Experienced in orchestrating end-to-end LLM workflows with Airflow/LangChain, improving reliability via monitoring/error handling, and driving measurable quality through retrieval and hallucination-focused evaluation metrics.”

“Built and deployed an LLM + RAG + memory system on a Furhat social robot, adding continuous face/voice recognition embeddings over WebSockets to enable persistent, natural conversations across sessions. Experienced working around real-world hardware/latency constraints and uses Datadog plus structured debugging/rollback practices for stabilizing customer-facing LLM workflows.”

“Full-stack engineer with primary depth in .NET Core and Python who has built and deployed end-to-end AWS applications (Lambda, API Gateway, S3, CloudFront) and supported them in production. Experienced in scaling large, data-driven workloads using queues/background workers, batching, and database tuning, with strong focus on API contracts, observability, and resilience patterns; also has hands-on React/TypeScript and some Spring Boot exposure.”