Vetted Java Professionals

“Capgemini engineer with hands-on ownership of production TypeScript backend integrations and loyalty-platform modernization. Built AWS event-driven microservices (SNS/SQS/Lambda) with GraphQL vendor calls and DynamoDB persistence, emphasizing reliability patterns like retries and idempotency; reports ~25% response-time improvement after migrating/optimizing services and workflows.”

“Data engineer at Fidelity who built and operated a real-time financial transactions lakehouse on AWS/Databricks, processing millions of records daily with Kafka streaming. Demonstrated strong reliability and data quality practices (watermarking, idempotent Delta writes, validation/reconciliation, observability) and delivered measurable improvements (~30% faster jobs and ~30% fewer data issues) while enabling trusted gold-layer analytics for downstream teams.”

“Built and deployed a live production LLM document Q&A platform (DocumindAI) with an adaptive RAG pipeline (Claude + Cohere embeddings + pgvector), source-cited structured outputs, and engineered fallbacks for reliability and sub-2s latency. Also has enterprise integration experience at Tech Mahindra working with messy IFS ERP XML integrations, using validation/normalization and JTA transactions to prevent partial writes and data corruption.”

“Backend engineer who optimized an AI-driven portfolio analytics/insights platform at Fidelity, addressing latency and traffic growth by moving services toward microservices, improving service communication, and tuning API/DB performance. Experienced scaling Python/FastAPI services with Docker + Kubernetes autoscaling, and strengthening security/privacy for sensitive client portfolio data used in LLM-based reporting.”

“Backend engineer who built and evolved a PHI-compliant RAG system (FastAPI + LangChain + embeddings/FAISS) for internal document search and summarization, delivering <400ms p95 latency at ~2,500 daily requests and measurable impact (30% faster investigations, +17% retrieval relevance). Demonstrates strong security and rollout discipline (RBAC/RLS/JWT, redaction/audits, shadow mode, dual writes, canaries) and a focus on reducing hallucination risk via grounded guardrails and confidence-based fallbacks.”

“Robotics software engineer focused on multi-robot fleet orchestration in ROS 2, owning the fleet manager and task dispatch layer for pick/drop workflows. Strong in real-world reliability and safety (heartbeats, idempotent tasking, E-stop/localization confidence gates) and in debugging timing/state issues via telemetry alignment and rosbag replay, with experience in simulation, CI/CD, Docker, and Kubernetes-based deployments.”

“Product-minded full-stack engineer at a B2B startup who ships high-stakes customer-facing features fast: delivered a Spanish AI support agent in 2 weeks by benchmarking LLMs and using native Spanish system prompts, reaching 90% resolution. Built the company’s first monetization system (hybrid subscription + usage) with Stripe/Firebase, emphasizing secure JWT-based flows and idempotent webhooks, and led a microservices decoupling effort that cut developer onboarding time by 50%.”

“Product-minded full-stack engineer from CouponDunia who owned end-to-end notification and recommendation services at million-user scale. Built internal admin/analytics and operations dashboards in React/TypeScript with typed contracts and scalable Node.js REST APIs, and has deep microservices experience with Kafka/RabbitMQ (idempotency, retries/DLQs, partitioning, consumer tuning, and observability).”

“Backend engineer from Optum who built and optimized a real-time, Kafka-driven healthcare claims processing platform handling 1M+ claims/month. Strong in reliability, state management, and observability for distributed systems, plus production deployment automation with Docker/Kubernetes and CI/CD; no direct ROS/robotics simulator experience yet but frames work in robotics-adjacent real-time principles.”

“Built and evolved a geospatial ETL + API platform that processes pixel-wise satellite imagery in PostgreSQL/PostGIS into low-latency farm-level time-series metrics for an interactive dashboard, using precomputed hotspot analysis to reduce latency by 75–80%. Experienced in FastAPI-style API contract design (OpenAPI), caching, server-side filtering/compression, and production-minded security patterns (RBAC, session-derived authorization, password hashing) with disciplined rollback/versioning practices.”

“Built an end-to-end wafer-data anomaly detection and reporting system at Samsung using PySpark, Random Forest models, SQL, and Grafana to help engineers track faults and take corrective action. Also has strong UX prototyping and validation practices in Figma plus hands-on front-end/full-stack experience (HTML/CSS/TypeScript), including a student project recognized as best design out of 25 teams, and early-stage startup experience pivoting a product based on user interviews into a real-time in-context feedback overlay.”

“Built and deployed a production LLM-powered workflow assistant that automated internal marketing/production business tasks (document summarization, repeated Q&A, status updates). Demonstrates end-to-end applied LLM engineering: modular RAG architecture, hallucination/latency mitigation, automated evals to prevent prompt regressions, and Azure-based orchestration (Functions/Logic Apps) with monitoring and controlled rollouts.”

“Backend/data engineer with hands-on production experience across FastAPI microservices and AWS data platforms. Has delivered serverless and Glue/EMR-based ETL pipelines with strong observability (Prometheus/Grafana/Sentry, CloudWatch/SNS), schema-evolution resilience, and measurable SQL performance wins (5 min to <30 sec). Open to onsite meetings in the Bethesda, MD area and flexible on remote arrangements.”

“Early-career engineer from BNP Paribas who drove a large-scale observability modernization—selecting and implementing Prometheus/Grafana for a 2000+ server estate, then productionizing it on Kubernetes via Docker/Jenkins. Known for hands-on demos, strong documentation/templates, and pragmatic troubleshooting (including custom Python metrics) that improved visibility and cut debugging time by ~60%.”

“Built and deployed AcademiQ Ai, a production LLM-based teaching assistant using GPT/BERT with RAG (LangChain + Pinecone) to handle large student notes and generate adaptive explanations/quizzes. Demonstrated measurable retrieval-quality gains (18% precision improvement, 22% less irrelevant context) by tuning similarity thresholds and chunking based on user satisfaction signals. Also orchestrated terabyte-scale, real-time demand forecasting pipelines using Airflow and Kubeflow on GCP with strong monitoring, shadow deployment, and feedback-loop practices.”

“Full-stack engineer who builds TypeScript/React SPAs on Python (Flask/FastAPI) backends and has hands-on experience integrating AI components (Azure OpenAI, LangChain, vector databases) into user workflows. Has built internal AI-enabled dashboards/search tools for analysts and business users, emphasizing typed API contracts, CI/CD-driven quality, and microservices reliability patterns (monitoring, retries, idempotency) at scale.”

“Software/IoT-focused candidate with startup internship experience building a planner AI service integrating Google Calendar (OAuth/token handling) and connecting AI, backend, frontend, and database. Also has embedded systems + AWS networking troubleshooting experience and has implemented TCP networking projects optimized for throughput and low jitter/latency; collaborates with clients via weekly meetings using Trello/Slack.”

“AI/LLM engineer who has shipped production RAG copilots and multi-agent workflows, including a real-time Llama3 (Ollama) copilot backend handling 12k+ concurrent queries at 99.9% uptime. Deep on orchestration (Langflow/Airflow/Kubernetes), reliability evaluation (hallucination detection, p95 latency, token cost), and monitoring (Prometheus/Grafana), with demonstrated stakeholder-facing analytics delivery via Tableau.”

“LLM/agentic systems engineer who built a production "Agentic AI Diagnostic Assistant" for network engineers, using a multi-agent Llama 2 + LangChain architecture with RAG over telemetry/incident data in DynamoDB and confidence-based deferrals to reduce hallucinations. Also has strong MLOps/orchestration experience (Airflow, EventBridge, Spark, Docker, SageMaker/ECS) at multi-terabyte/day scale and delivered multilingual NLP analytics (fine-tuned BERT/spaCy) for support operations through hands-on stakeholder workshops.”

“Software engineer/product owner experience at UnitedHealth Group owning a high-volume claims eligibility console end-to-end (React/TypeScript + Spring Boot microservices) processing 1M+ transactions/day. Strong in event-driven architecture (Kafka/RabbitMQ), HIPAA-aligned security (OAuth/JWT/RBAC), and building internal observability tools that improve incident triage and production reliability.”

“Frontend engineer in an insurance SaaS white-label environment who transformed a fragmented ecosystem of 100+ duplicated React repos into a scalable platform using versioned NPM libraries (CommonWeb/WorkflowWeb). Built a JSON-driven, multi-step quote and payment workflow in React+TypeScript with Redux-Saga for complex async orchestration and reliability (idempotency, retries, takeLatest). Delivered measurable impact: 35% bundle reduction, onboarding cut from weeks to days, and bug fixes propagated across clients in hours.”

“Full-stack engineer with financial services experience (Lincoln Financial) who owned a customer-facing financial portal end-to-end using TypeScript/React and Node/Express. Has hands-on microservices and RabbitMQ event-driven workflows, addressing scale issues like retries/duplicates with idempotency and traceable logging, and built an internal real-time ops/support dashboard to improve monitoring and incident response.”

“Full-stack engineer who has owned customer-facing and internal web portals end-to-end (API, database, React UI, and deployment). Experienced designing multi-service architectures with Node/Express and Java/Spring Boot plus RabbitMQ/Kafka messaging, emphasizing contract/versioning discipline, observability, and operational tooling that measurably reduces support load and manual work.”