Vetted Java Professionals

“University Rover Competition autonomous-systems lead who architects and debugs a full ROS 2 autonomy stack (Nav2, vSLAM, EKF fusion) and backs it with strong engineering hygiene (Docker + GitHub Actions CI running headless Gazebo and colcon tests). Also has industry-facing ROS 2 hardware integration experience, building a ros2_control plugin for a Unitree G1 arm using CycloneDDS and optimizing real-time behavior via QoS tuning.”

“Backend engineer with insurance/claims domain experience who modernized legacy claims processing systems to support AI-assisted claim review. Emphasizes production-ready API design in Python/FastAPI (schemas, async, caching, graceful degradation), strong observability with Prometheus, and layered security including JWT auth plus database row-level security (Supabase/Postgres).”

“Backend Python engineer who built core services for a telecom automation engine monitoring thousands of routers in real time and auto-generating support tickets. As the sole Intelygenz engineer on the project, they diagnosed a costly Terraform/GitLab CI/CD resource-leak issue in AWS and implemented a cleanup redesign that eliminated orphaned resources and reduced client cloud spend. Also shipped applied-AI ticket triage suggestions via API integration and built an end-to-end Gmail-to-ticket ingestion workflow.”

“Full-stack + ML engineer who built “Finsight,” a real-time financial risk platform (React/FastAPI/MongoDB/AWS Lambda) processing 2M+ records monthly, using sharding and Redis caching (60% DB load reduction) plus async and batch optimizations. Also has healthcare product experience at Apollo Healthcare, partnering directly with clinicians/admins to design and iterate EHR dashboards via Figma prototyping and user testing, and demonstrates clear system design thinking for real-time voice-to-LLM architectures.”

“DevOps/GCP-focused engineer with experience helping move complex/LLM-style prototypes toward production by clarifying requirements, hardening architecture, and driving OS-level test remediation to full pass rates. Debugs LLM/agentic workflow issues like distributed systems using GCP observability (Cloud Logging/Monitoring, GKE metrics) and implements alerting policies for proactive communication. Has delivered internal DevOps training from basics through end-to-end GCP infrastructure and deployment, improving engagement with real-world examples and analogies.”

“Backend engineer with experience in fraud reporting and billing systems, building Java/Spring Boot services behind a React frontend and improving performance 40%+ with caching and SQL optimization while maintaining 99.9% uptime. Has hands-on experience migrating a monolith to microservices with incremental rollout, clear data ownership boundaries, and production-grade API reliability/security practices (JWT/OAuth, RBAC, row-level scoping).”

“Backend/data engineer who reports building production Python services (FastAPI + JWT) backed by Postgres and Redis, and modernizing data workflows using AWS Glue + PySpark with S3/RDS. States experience delivering AWS solutions (S3, SES, Cognito) and using golden datasets/snapshot testing for migration parity, with many details withheld due to NDAs. Seeking fully remote work with a $300k base salary expectation.”

“Robotics software engineer focused on backend and distributed systems for real-time robot operations, including sensor ingestion, robot state management, and robot-to-cloud communication. Hands-on with ROS/ROS2 integration and real-time navigation debugging, plus production-grade monitoring, CI/CD, and containerized deployments (Docker/Kubernetes) to improve stability and performance.”

“Backend-focused Python engineer who has owned production FastAPI services deployed on Kubernetes, including CI/CD (GitLab CI to ECR) and GitOps delivery via ArgoCD/Helm. Has hands-on experience with complex reliability and infrastructure work—solving data inconsistency with validation/partial-data paths, fixing K8s liveness issues via lazy loading, and supporting a phased cloud-to-on-prem migration with dual-writes and monitoring. Also built Kafka-based real-time ingestion consumers handling bursty, high-throughput traffic with async processing and topic/retention tuning.”

“Built a production AI-powered customer support Q&A system using an internal knowledge base to reduce repetitive ticket work and improve customer satisfaction, with an emphasis on source-backed answers and expert oversight. Also has experience defining deployment services in a microservices architecture and integrating large-scale APIs (including work connected to US HHS/COVID-19).”

“Built and productionized a predictive maintenance system (predictEngineLife) estimating Remaining Useful Life for PW4000 turbofan engines from large-scale, noisy telemetry—emphasizing modular pipeline design, deterministic preprocessing, and strong observability/guardrails. Also has hands-on experience diagnosing multi-agent LLM customer-support workflows (schema/state issues, fallback paths, regression tests) and has led developer workshops (GDG Pune) while partnering with sales teams on technical discovery and POCs.”

“Backend engineer with experience in both healthcare (Siemens) and payments (Bitwise), focused on scaling Python APIs and modernizing architectures. Has led monolith-to-microservices migrations and introduced Kafka async processing, Redis caching, and ELK observability, citing ~40% faster issue resolution and improved reliability via idempotency and strong security controls (OAuth2/JWT, RBAC, RLS).”

“Built and deployed a production LLM-powered support assistant for customer support agents using a RAG architecture over internal docs and past tickets, with human-in-the-loop review. Demonstrates strong applied LLM engineering focused on real-world constraints (hallucinations, latency, cost) using routing to smaller models, reranking, caching, and rigorous evaluation/monitoring (offline eval sets, A/B tests, KPI tracking).”

“Internship experience shipping production AI systems: built an end-to-end RAG platform (Python/FastAPI + LangChain/LangGraph + vector search) to answer support questions from unstructured internal docs, with a strong focus on hallucination prevention through confidence gating and rigorous offline/online evaluation. Also delivered an AI-driven personalization/analytics feature using an unsupervised clustering pipeline, iterating with PMs to align statistically strong clusters with actionable business segmentation.”

“Full-stack developer with 4 years of experience and an MS in Computer Science who led frontend delivery for a large airline platform (booking, check-in, and payment flows) using Angular/TypeScript with a Java backend. Emphasizes quality at scale via SonarQube monitoring, E2E/regression testing, and iterative Agile collaboration with clients using Figma.”

“Built and deployed a production Task Prioritization App using Python/Streamlit/MongoDB with Gemini API to score and rank tasks by context (deadlines, dependencies, urgency). Focused on reliability challenges like prompt tuning for nuanced task understanding, concurrent DB updates, and performance via async LLM calls, and validated usability through iterative feedback with a non-technical end user.”

“Software engineer (Yellow.ai) who built and productionized an AI-driven resume tailoring system using embeddings + Chroma RAG + QLoRA fine-tuning, deployed via Docker/Kubernetes with CI/CD on a CPU-only Oracle VM. Demonstrates strong reliability/evaluation rigor (custom hallucination/coverage/relevance metrics) and measurable business impact, including a 60% user satisfaction lift from improving chatbot intent accuracy with product and support teams.”

“Internship project at Builder Market: built an end-to-end production multimodal LLM application that estimates renovation/replacement costs from appliance photos (CLIP embeddings) or text descriptions, combining fine-tuning with agentic RAG. Focused heavily on real-world performance constraints—latency and cost—using parallel agent workflows, model routing to smaller/open-source models, re-ranking, and retrieval chunking, and collaborated closely with CEO/co-founders to deliver the solution.”

“AI/LLM engineer who built a production RAG-based Text2SQL engine using Qdrant, including creating the underlying business/DB documentation, generating a test dataset, and designing detailed SQL-quality metrics for validation. Also partnered with non-technical stakeholders on a speech recognition project to prioritize medical terminology, improving accuracy through targeted corpora, lookup-table correction, and fine-tuning with a modified loss function.”

“Built and deployed a real-time hospital readmission risk prediction system at NYU Langone Health, combining structured EHR data with BERT-based NLP on clinical notes and serving predictions to clinicians via Azure ML and FHIR APIs. Emphasizes production reliability and clinical trust through SHAP-based explainability and robust healthcare data preprocessing, and reports a 22% reduction in 30-day readmissions.”

“AI/ML Engineer at Fifth Third Bank who has shipped production fraud detection and risk analysis systems combining ML models with LLM-powered insights/explanations, including real-time monitoring, drift detection, and automated retraining under regulatory explainability constraints. Also built a hybrid-retrieval internal knowledge-base QA system (+20% top-5 relevance) and delivered a customer support chatbot that reduced first response time by 30% through strong stakeholder collaboration.”

“Game developer who implemented the battle simulation/progression system for "Gladiator Imperium," focusing on turn logic, stat-driven combat, and player-facing feel through UI and camera polish. Also has experience modernizing a 10+ year legacy project by refactoring into new frameworks and even migrating to a different programming language, leveraging AI to interpret undocumented code.”

“Frontend-focused engineer who led a full-scale CMS/dashboard build using React (with TypeScript), plus Node.js microservice APIs on AWS Lambda and MySQL. Emphasizes scalable component architecture, feature-based code organization, performance profiling via Chrome DevTools, and disciplined release practices (CI/CD, UAT gating, production monitoring) in fast-paced delivery cycles.”

“Frontend engineer who has led mobile-first and web React/TypeScript products end-to-end, including an expense tracking app handling sensitive financial data and a real-time messaging/activity dashboard with chat, presence, and contextual side panels. Emphasizes scalable architecture, rigorous component-boundary testing, and production-safe rollout practices (feature flags, analytics/logging, staged releases) to ship reliably in fast-paced environments.”