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I'm a Principal Engineer with 20+ years building enterprise systems that stay up, now focused on production AI: AI agents, LLM applications, and RAG. I ship agentic workflows, retrieval pipelines, and LLM integrations on rock-solid Java + AWS foundations — engineered with the rigor to survive real load, real users, and real scrutiny, not just impress in a proof-of-concept. ⚡ AI Agents · LLM Apps · RAG · MCP · Java · Spring Boot · Kafka · AWS PLATFORM ENGINEERING & ARCHITECTURE ▸ Backend & distributed systems — Java/Kotlin (Spring Boot) as the core, plus Python (FastAPI). Event-driven microservices, Kafka pipelines, REST and GraphQL APIs, PostgreSQL. Systems designed to scale, fail gracefully, and pass security review. ▸ Cloud & platform engineering — AWS, Docker, Kubernetes, Terraform, CI/CD. Reusable platform patterns adopted across multiple teams. ▸ Technical leadership — 20+ years leading architecture and hands-on delivery; guided teams from 10 to 55+ engineers across multiple time zones. AI, LLM & AUTOMATION ▸ AI agents & agentic workflows — multi-step agents with LangChain and LangGraph. Tool calling, structured outputs, error recovery, and MCP (Model Context Protocol) servers that expose your tools and data to LLMs cleanly. Agents that complete real tasks, not chatbots that loop. ▸ Production RAG — hybrid search (BM25 + semantic), vector databases (pgvector, Pinecone, Weaviate, OpenSearch), grounding guardrails and evaluation so your AI cites real sources, not hallucinations. ▸ LLM integration — AWS Bedrock, Anthropic Claude, OpenAI. Prompt versioning, JSON-schema enforcement, and CI/CD regression evals so prompts do not silently break when you ship. ▸ AI automation — wiring LLMs and agents into existing business systems to remove manual work, with auditable, deterministic results. END-TO-END DELIVERY ▸ The platform and the product around it — my core is backend and platform (Java, Kafka, AWS) plus the AI running on it, and I take it all the way to a working product with React/Next.js when a project needs it. One senior engineer who owns the platform, the AI, and the deployment — no coordinating between a backend dev, an AI engineer, and a DevOps engineer. WHAT YOU GET WORKING WITH ME ▸ Real production delivery — monitoring, evaluation, and guardrails. Not notebooks. Not demos. ▸ Engineering judgment from 20+ years of distributed systems — whether the job is a Java platform, an AWS build-out, or an AI agent, it sits on infrastructure designed to scale and pass security review. ▸ Regulated-environment fluency — PII handling, audit trails, compliance constraints, and security review are familiar territory (financial-services background), not new problems to solve on your project. PROJECTS I DELIVER WELL ▸ Designing and building scalable backends, APIs, and event-driven platforms ▸ AWS architecture, cloud migration, and infrastructure-as-code ▸ Turning an AI prototype or proof-of-concept into a real production system ▸ Building LLM agents, RAG search, and document extraction into existing applications ▸ AI automation of manual business workflows ▸ Building for regulated industries (finance, healthcare, legal) with compliance built in CORE STACK Languages & Backend · Java · Kotlin · Spring Boot · Python · FastAPI · Node.js · TypeScript · REST · GraphQL · Microservices · Apache Kafka · Event-Driven Architecture Cloud & Platform · AWS · AWS Bedrock · Kubernetes · Docker · Terraform · CI/CD AI & LLM · LLMs · RAG · LangChain · LangGraph · MCP · AI Agents · OpenAI · Anthropic Claude · Vector Databases (pgvector · Pinecone · Weaviate · OpenSearch) · Prompt Engineering · LLM Evaluation Frontend · React · Next.js · TypeScript · Tailwind CSS Data · PostgreSQL · MongoDB · Redis · pgvector HOW WE START Send me a short message describing your project. I respond within a few hours during business days. If it looks like a good fit, we book a free 20-minute scoping call where I give you an honest read on feasibility, approach, and timeline — whether you hire me or not.

I’m building a room-aware clinical voice system that lets doctors ask questions about the patient in front of them and receive real-time answers from the chart. The hard part isn’t making an LLM talk. It’s proving the system has the right patient, the right evidence and the right authority before it answers or acts. CURRENT: VOICE + AGENTIC EMR For a multi-facility medical clinic in Dallas, I’m leading the AI and EMR architecture behind a purpose-built voice device. It combines room proximity, clinician identity and active encounter data to bind the correct doctor, room and patient before accepting a question. A doctor can ask, “What was her last A1c?”, “Why was this medication stopped?” or “Did she complete the cardiology follow-up?” and receive a low-latency answer assembled from structured EMR records and longitudinal clinical notes. The answer is designed to show its evidence, dates and conflicts—and abstain when the chart does not support a reliable conclusion. The same platform captures the encounter, separates clinician and patient speech, transcribes and translates multilingual conversations, and prepares chart-ready documentation. We’re extending it into governed EMR agents that can identify unfinished follow-ups, prepare referrals and orders, assemble prior-authorization evidence, coordinate scheduling, draft patient instructions and reconcile documentation. Underneath the interface are FHIR/HL7 integrations, patient and encounter identity resolution, permissioned tool calls and source-level auditability. The operating model is simple: AI does the searching, assembling and drafting; the doctor reviews and verifies. Read, prepare and act are separate permissions. Consequential actions require approval, an audit trail and verification that the EMR actually changed. In parallel, I’m building the dialect-rich, human-reviewed Arabic speech data and evaluation pipeline needed to post-train open-weight ASR models. The roadmap includes LoRA adaptation, distillation and quantized serving for lower-cost self-hosting and possible edge deployment. SELECTED PROOF • For Plan AI, I built and productionized a real-estate intelligence engine that finds and interprets zoning rules, classifies interior, corner and through lots from geospatial data, calculates setbacks and buildable envelopes, and incorporates FEMA flood risk. Its evaluation harness catches invented ordinances, invalid geometry and unsupported conclusions—allowing cheaper models such as Gemini Flash to be used while still returning verifiably correct results. • For a publicly traded lender with approximately $40M+ in annual revenue, I led an AI underwriting platform that automated most small-business credit decisions while routing the hardest 10–15% to expert underwriters. Confidence thresholds, escalation, PII isolation and auditability were built into the workflow. I work best where AI touches money, care, compliance or operations and an impressive demo is not enough. I can move from executive conversation to architecture, production code, evaluation and rollout without the handoffs of a conventional consulting team. As one client put it: “Got a week’s worth of work done in less than an hour due to Jonathan’s expertise.”

Need help solving a difficult engineering, AI, scientific, or research problem? I help companies, startups, universities, and research teams transform complex ideas into practical, technically rigorous solutions. I'm a PhD Physicist, Research Scientist, and Engineering Consultant with more than 20 years of interdisciplinary experience helping companies, startups, researchers, engineers, healthcare professionals, and graduate students solve complex technical problems. Highlights ✔ Published in Nature Communications ✔ Published in PNAS ✔ Published in Journal of Biological Chemistry ✔ Former Research Scientist — Cornell University ✔ Former Research Scientist — Duke University Medical Center ✔ Principal Investigator using NSF ACCESS HPC I specialize in transforming complex ideas into practical, technically rigorous, and well-documented solutions by combining scientific research, engineering, artificial intelligence, and computational modeling. I can help you with ✔ Artificial Intelligence & Machine Learning ✔ Python Programming & Scientific Computing ✔ Data Science & Statistical Analysis ✔ Engineering Design & Numerical Simulation ✔ Computational Physics & Applied Mathematics ✔ Biomedical Engineering & Medical Imaging ✔ MATLAB, Scientific Visualization & Image Analysis ✔ Research Consulting & Experimental Design ✔ Technical Reports, Scientific Publications & Literature Reviews ✔ Grant Proposals (NSF, SBIR/STTR) & Technical Documentation Why clients choose to work with me • PhD in Physics with interdisciplinary expertise spanning engineering, AI, biomedical research, data science, and scientific computing. • Research experience at Cornell University and Duke University Medical Center. • Published author in internationally recognized scientific journals. • University faculty experienced in mentoring engineers, researchers, and technical teams. • Strong reputation for developing structured, practical solutions and explaining complex technical concepts clearly. • Every project is approached with scientific rigor, attention to detail, professionalism, and clear communication. Whether you need to develop an AI model, analyze scientific data, design an engineering system, perform computational simulations, prepare a technical report, review a research manuscript, or solve a challenging interdisciplinary problem, I will work closely with you to deliver accurate, high-quality, and professional results. If you're looking for a research scientist who can bridge science, engineering, and AI to solve complex technical challenges, I'd be happy to discuss your project.

I build AI systems that make it to production: machine learning and NLP pipelines, LLM and RAG applications, AI agents, and voice AI used by real customers every day. 𝐑𝐞𝐜𝐞𝐧𝐭 𝐖𝐨𝐫𝐤 - Voice AI agent platform at a healthcare technology company - Clinical document extraction system on vLLM hitting 99.99%+ accuracy on messy, unstructured files - Internal agentic coding assistant that cut time spent on repetitive engineering workflows by 80% - LiveQ, an AI desktop assistant I founded (Electron and Next.js on LiveKit): designed the full agent architecture and ran 50+ customer interviews in the first month 𝐌𝐋 𝐚𝐧𝐝 𝐍𝐋𝐏 𝐁𝐚𝐜𝐤𝐠𝐫𝐨𝐮𝐧𝐝 My experience goes deeper than the LLM wave. At Penn State's NLP lab I built a conversational agent deployed to Alexa devices reaching a 50M+ user base, and worked hands-on with transformer models (BERT, T5, XLNet), NER pipelines, OCR, and topic modeling. That history means I know when your problem needs a fine-tuned classifier instead of a frontier model, and when it doesn't need ML at all. 𝐖𝐡𝐚𝐭 𝐈 𝐂𝐚𝐧 𝐇𝐞𝐥𝐩 𝐖𝐢𝐭𝐡 - LLM applications and RAG pipelines with strict accuracy targets - AI agents and tool integrations (function calling, MCP) - Voice AI and real-time interaction systems - NLP and document AI: extraction, classification, intelligent OCR - End-to-end automation, from backend services to a polished UI 𝐒𝐭𝐚𝐜𝐤 𝐚𝐧𝐝 𝐂𝐫𝐞𝐝𝐞𝐧𝐭𝐢𝐚𝐥𝐬 Python, TypeScript, LangChain, LiveKit, Ray Serve, vLLM, Next.js, AWS and GCP. MS in Computer Science (AI) from USC. 𝐇𝐨𝐰 𝐈 𝐖𝐨𝐫𝐤 I move fast, take ownership, and communicate clearly. Send me a message with what you're building, and I'll tell you honestly whether I'm the right fit and how I'd approach it. Keywords: Artificial Intelligence, Machine Learning, Deep Learning, NLP, Natural Language Processing, Generative AI, LLM, Large Language Models, ChatGPT, OpenAI, Claude, Llama, RAG, Retrieval Augmented Generation, Vector Database, Embeddings, AI Agent, Agentic AI, Multi-Agent Systems, MCP, Model Context Protocol, Function Calling, Voice AI, Conversational AI, Chatbot, Speech-to-Text, Text-to-Speech, LiveKit, vLLM, LangChain, Ray Serve, Prompt Engineering, LLM Deployment, Document AI, Intelligent Document Processing, Data Extraction, OCR, Named Entity Recognition, BERT, Transformers, AI Automation, Workflow Automation, Python, TypeScript, Next.js, React, Electron, AWS, GCP, Healthcare AI, Full-Stack Development, Real-Time Systems

𝗬𝗼𝘂'𝗿𝗲 𝗻𝗼𝘁 𝗷𝘂𝘀𝘁 𝗵𝗶𝗿𝗶𝗻𝗴 𝗮 𝗱𝗲𝘃𝗲𝗹𝗼𝗽𝗲𝗿, 𝘆𝗼𝘂'𝗿𝗲 𝘂𝗻𝗹𝗼𝗰𝗸𝗶𝗻𝗴 𝗮 𝗳𝘂𝗹𝗹-𝘀𝘁𝗮𝗰𝗸 𝗔𝗜 𝗰𝗮𝗽𝗮𝗯𝗶𝗹𝗶𝘁𝘆. I deliver end-to-end intelligent products with the speed and firepower of a seasoned engineering operation behind every project. When a project demands it, 𝗜 𝗺𝗼𝗯𝗶𝗹𝗶𝘇𝗲 𝘁𝗵𝗲 𝗿𝗶𝗴𝗵𝘁 𝘀𝗽𝗲𝗰𝗶𝗮𝗹𝗶𝘀𝘁𝘀, AI engineers, mobile devs, and designers, so your deadline never depends on a single point of failure. You get one accountable lead and the horsepower to match any scope. As former CTO of LinkedUnion, I shipped AI-driven workforce solutions at scale. 𝗜 𝗯𝗿𝗶𝗻𝗴 𝘁𝗵𝗮𝘁 𝘀𝗮𝗺𝗲 𝗽𝗿𝗼𝗱𝘂𝗰𝘁 𝗼𝘄𝗻𝗲𝗿𝘀𝗵𝗶𝗽 𝗮𝗻𝗱 𝘀𝘁𝗿𝗮𝘁𝗲𝗴𝗶𝗰 𝗲𝘅𝗲𝗰𝘂𝘁𝗶𝗼𝗻 𝘁𝗼 𝗲𝘃𝗲𝗿𝘆 𝗲𝗻𝗴𝗮𝗴𝗲𝗺𝗲𝗻𝘁, no hand-waving, no shortcuts. ----------------------------- 𝗪𝗛𝗔𝗧 𝗜 𝗕𝗨𝗜𝗟𝗗 𝗙𝗢𝗥 𝗬𝗢𝗨 ----------------------------- 🤖 𝗔𝗜 & 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝘁 𝗦𝘆𝘀𝘁𝗲𝗺𝘀 𝗟𝗟𝗠 𝗶𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻𝘀, 𝗥𝗔𝗚 𝗽𝗶𝗽𝗲𝗹𝗶𝗻𝗲𝘀, 𝗔𝗜 𝗮𝗴𝗲𝗻𝘁𝘀 built for real users, not just demos. OpenAI / Claude / Gemini APIs, prompt engineering, vector databases (Pinecone, Weaviate), and intelligent automation wired into your product. ➡ OpenAI & Claude APIs · LangChain / LlamaIndex · RAG pipelines · AI agents · Vector DBs · Prompt engineering 💻 𝗙𝘂𝗹𝗹 𝗦𝘁𝗮𝗰𝗸 𝗪𝗲𝗯 & 𝗠𝗼𝗯𝗶𝗹𝗲 𝗣𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻-𝗴𝗿𝗮𝗱𝗲 𝗽𝗹𝗮𝘁𝗳𝗼𝗿𝗺𝘀, 𝘀𝗰𝗮𝗹𝗮𝗯𝗹𝗲 𝗔𝗣𝗜𝘀, 𝗮𝗻𝗱 𝗰𝗿𝗼𝘀𝘀-𝗽𝗹𝗮𝘁𝗳𝗼𝗿𝗺 𝗮𝗽𝗽𝘀, clean architecture from frontend to cloud, with real-time features and performance baked in from day one. ➡ React.js / Next.js · Django / FastAPI / Node.js · Flutter / React Native · PostgreSQL / Firebase · AWS / GCP / Docker · CI/CD 🎨 𝗨𝗜/𝗨𝗫 𝗗𝗲𝘀𝗶𝗴𝗻 & 𝗣𝗿𝗼𝗱𝘂𝗰𝘁 𝗧𝗵𝗶𝗻𝗸𝗶𝗻𝗴 𝗜 𝗱𝗲𝘀𝗶𝗴𝗻 𝗮𝗻𝗱 𝗯𝘂𝗶𝗹𝗱, nothing is lost in translation between mockup and shipped product. User-centered design that turns complex workflows into clean, intuitive interfaces your users will actually enjoy. ➡ Figma & Prototyping · Design systems · Responsive UI · User flow mapping · Component libraries ------------------------------------------- 𝗪𝗛𝗬 𝗖𝗟𝗜𝗘𝗡𝗧𝗦 𝗞𝗘𝗘𝗣 𝗖𝗢𝗠𝗜𝗡𝗚 𝗕𝗔𝗖𝗞 ------------------------------------------- ✅ 𝗗𝗲𝗮𝗱𝗹𝗶𝗻𝗲-𝗳𝗶𝗿𝘀𝘁 𝗺𝗶𝗻𝗱𝘀𝗲𝘁 - I plan for risk, not just the happy path ✅ 𝗔𝗜 𝗳𝗹𝘂𝗲𝗻𝗰𝘆 𝗮𝗰𝗿𝗼𝘀𝘀 𝘁𝗵𝗲 𝘀𝘁𝗮𝗰𝗸 - not just API calls, but product-grade integration ✅ 𝗙𝘂𝗹𝗹 𝗼𝘄𝗻𝗲𝗿𝘀𝗵𝗶𝗽 - from wireframe to production deploy, one point of contact ✅ 𝗧𝗿𝗮𝗻𝘀𝗽𝗮𝗿𝗲𝗻𝘁 𝗮𝘀𝘆𝗻𝗰 𝗰𝗼𝗺𝗺𝘂𝗻𝗶𝗰𝗮𝘁𝗶𝗼𝗻 - no chasing for updates ✅ 𝗦𝗰𝗮𝗹𝗮𝗯𝗹𝗲 𝗰𝗮𝗽𝗮𝗰𝗶𝘁𝘆 - the right expertise is always available when your project needs it ✅ 𝗖𝗧𝗢-𝗹𝗲𝘃𝗲𝗹 𝘀𝘁𝗿𝗮𝘁𝗲𝗴𝗶𝗰 𝘁𝗵𝗶𝗻𝗸𝗶𝗻𝗴 - when scoping your product, I think like an owner ---------------------- 𝗣𝗥𝗢𝗩𝗘𝗡 𝗥𝗘𝗦𝗨𝗟𝗧𝗦 ---------------------- ➡ 𝗕𝘂𝗶𝗹𝘁 𝗮𝗻𝗱 𝘀𝗵𝗶𝗽𝗽𝗲𝗱 𝗮𝗻 𝗔𝗜-𝗱𝗿𝗶𝘃𝗲𝗻 𝘄𝗼𝗿𝗸𝗳𝗼𝗿𝗰𝗲 𝗲𝗻𝗴𝗮𝗴𝗲𝗺𝗲𝗻𝘁 𝗽𝗹𝗮𝘁𝗳𝗼𝗿𝗺 𝗮𝘀 𝗖𝗧𝗢 at LinkedUnion, improving team collaboration and productivity at scale. ➡ 𝗗𝗲𝗹𝗶𝘃𝗲𝗿𝗲𝗱 𝗵𝗶𝗴𝗵-𝘁𝗿𝗮𝗳𝗳𝗶𝗰 𝘄𝗲𝗯 𝗽𝗹𝗮𝘁𝗳𝗼𝗿𝗺𝘀 in React, Django, and Next.js with performance-optimized rendering and modern component-driven UI. ➡ 𝗦𝗵𝗶𝗽𝗽𝗲𝗱 𝗰𝗿𝗼𝘀𝘀-𝗽𝗹𝗮𝘁𝗳𝗼𝗿𝗺 𝗺𝗼𝗯𝗶𝗹𝗲 𝗮𝗽𝗽𝘀 with offline sync, push notifications, and full app store deployment across iOS and Android. ➡ 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝗲𝗱 𝘇𝗲𝗿𝗼-𝗱𝗼𝘄𝗻𝘁𝗶𝗺𝗲 𝗖𝗜/𝗖𝗗 𝗽𝗶𝗽𝗲𝗹𝗶𝗻𝗲𝘀 with Docker containerization and Datadog monitoring across multiple production environments. ------------------------------------------------------------ 𝗥𝗲𝗮𝗱𝘆 𝘁𝗼 𝗯𝗿𝗶𝗻𝗴 𝘆𝗼𝘂𝗿 𝗔𝗜 𝗼𝗿 𝘀𝗼𝗳𝘁𝘄𝗮𝗿𝗲 𝗽𝗿𝗼𝗱𝘂𝗰𝘁 𝘁𝗼 𝗹𝗶𝗳𝗲? Message me, I respond within hours, not days. Let's scope it together. ------------------------------------------------------------

Charlie Maere is a seasoned Information Technology expert with over 18 years of senior-level experience. He currently serves as the Global Digital Health and Data Analytics Director at the Elizabeth Glaser Pediatric AIDS Foundation. His areas of expertise span across multiple domains, including: Project Management Software Development, with proficiency in: Languages & Frameworks: Python, PHP, Angular, Ionic, Java, C++, Swift, C, C#, Ruby on Rails, JavaScript, Android, Flutter, React, Vuejs, nodejs. Hybrid/Mobile App Development Web Development Artificial Intelligence and Computer Vision, including: Retrieval-Augmented Generation (RAG) Large Language Models (LLMs) Computer Vision Predictive Modeling Classical Machine Learning Algorithms Firmware Development Cloud Computing, with experience in: AWS (Amazon Web Services) Microsoft Azure Systems Administration and Cybersecurity Strategic and Operational Planning Organizational Design and Scalable Network Architecture Information Systems and Machine Learning Collaborative Tools and ICT System Development Charlie’s work is driven by a passion for innovation and digital transformation, particularly in strengthening ICT infrastructure and data-driven solutions within global health and development ecosystems.