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I am a versatile Lead Software Engineer with over 10+ years of experience in developing high-performance, scalable, and secure software solutions. My expertise spans across multiple programming languages, including Java, Golang, Python, and JavaScript/TypeScript, allowing me to tackle diverse projects and deliver exceptional results. Throughout my career, I have successfully architected and developed numerous applications, leveraging cutting-edge technologies such as Spring Boot, Django, Gin, ReactJS, gRPC, and Apache Kafka. I have a deep understanding of microservices architecture, RESTful APIs, and event-driven systems, enabling me to design efficient and maintainable software solutions. As a cloud and DevOps expert, I have extensive experience working with AWS and GCP, utilizing services like EC2, Lambda, S3, and AppEngine to build highly available and scalable infrastructures. I am proficient in containerization technologies like Docker and have hands-on experience with CI/CD pipelines, using tools such as Jenkins, Ansible, and Git. Key Strengths: ✅ Architecting and developing microservices using Java, Spring Boot, and Spring Cloud ✅ Building high-performance applications using Golang and Python ✅ Developing interactive front-end applications with ReactJS and JavaScript/TypeScript ✅ Designing and implementing RESTful APIs, utilizing tools like Swagger and OpenAPI ✅ Integrating message queues and streaming platforms like Apache Kafka and RabbitMQ ✅ Implementing secure authentication and authorization using Spring Security, OAuth2, and JWT ✅ Leveraging AWS and GCP for cloud-based deployments and infrastructure management ✅ Implementing CI/CD pipelines and automating deployments with Docker, Jenkins, and Ansible I have a proven track record of leading and mentoring teams, ensuring the delivery of high-quality software solutions. My strong problem-solving skills, coupled with my ability to effectively communicate with both technical and non-technical stakeholders, allow me to drive projects to success. In addition to my professional experience, I have continuously invested in expanding my knowledge and staying up-to-date with the latest industry trends. I have successfully completed several Udacity Nanodegree programs, including: ✅ Intermediate Python Nanodegree (Mar. 2024) ✅ C++ Nanodegree (Feb. 2024) ✅ Golang Nanodegree (Feb. 2024) ✅ React Nanodegree (May 2022) ✅ Intermediate JavaScript Nanodegree (May 2022) ✅ Cloud DevOps Engineer Nanodegree (Oct. 2021) ✅ Full Stack JavaScript Developer Nanodegree (Sep. 2021) ✅ Data Streaming Nanodegree (Jul. 2021) ✅ AWS Cloud Architect Nanodegree (Jul. 2021) These Nanodegree programs have equipped me with advanced skills in Python, C++, Golang, React, JavaScript, Cloud DevOps, Full Stack Development, Data Streaming, and AWS Cloud Architecture. By constantly updating my knowledge and skill set, I ensure that I can deliver cutting-edge solutions and adapt to the ever-evolving technology landscape. If you are looking for a skilled Lead Software Engineer who can bring a wealth of experience, expertise, and a commitment to continuous learning to your projects, I am confident that my skills and knowledge make me an ideal candidate. I am excited about the opportunity to contribute to your organization's success and deliver innovative software solutions that drive business growth and exceed expectations.

I build AI-powered applications that ship to production and survive contact with real users. 𝟏𝟔 𝐲𝐞𝐚𝐫𝐬 of full-stack engineering, now focused on AI agents, RAG, and LLM integrations. I work on a .NET, React, and Angular foundation, which means I can also handle the parts that aren't glamorous: auth, deployment, databases, and a UI that doesn't make users cry. WHAT I BUILD ▸ AI Agents. Multi-step, tool-using agents that actually finish what you start them on. ▸ RAG Applications. Chat-with-your-docs, internal knowledge assistants, semantic search over private data. ▸ LLM Integrations. Adding GPT, Claude, Gemini, or open models into existing apps without breaking the rest of the codebase. ▸ Full-stack web apps. Angular or React on the front, .NET on the back, cloud-native on Azure or AWS. ▸ Legacy modernization. Moving 15-to-20-year-old codebases into the present. I've done this three times, including a beloved baseball simulator with millions of simulated games. STACK I WORK IN Backend: .NET 8, C#, ASP.NET Core, Entity Framework, Python, Go, Java Frontend: React, Angular, TypeScript, RxJS, Storybook, design systems AI: OpenAI, Anthropic Claude, Google Gemini, LangChain, vector databases, RAG pipelines, agent frameworks Data: SQL Server, Redis, MongoDB Cloud: Azure (Web Apps, Functions, SQL, Storage), AWS (Lambda, EKS), Terraform, Kubernetes Auth: JWT, OAuth, Auth0, ASP.NET Core Identity RECENT RESULTS ✓ Built and shipped a Google Gemini-powered AI system for automated outbound patient communications inside a physical therapy EMR platform, deployed across a network of rehabilitation hospitals and university health systems. ✓ Rebuilt a 20-year-old baseball simulation app (millions of simulated games, loyal user base) from classic ASP to .NET 8 and Angular on Azure. Improved 90-day user retention by over 10% and unlocked a new design system for the product team. ✓ Architected and shipped a multi-tenant SaaS platform for the event registration industry, migrating from on-prem data centers to Azure PaaS. Grew revenue 10% through direct client work and cut IT infrastructure spend by 40%. ✓ Led cloud architecture for a national crop insurance carrier across AWS and Azure. Set up Terraform-managed infrastructure, mentored a team of dev leads, and shipped a Figma-to-production design system bridging design, product, and engineering. WHAT A RECENT CLIENT SAID "I hired Adam specifically because of his wide variety of experience and his profound level of skill. Over 18 months he proved himself to be an active and helpful member of the team. His versatility and engagement was crucial to our growth. I would enthusiastically recommend him." — Jason, BaseHit HOW I WORK I show up, I listen, I write code that holds up under load. I'm comfortable being the senior voice in the room or the quiet pair of hands, whichever the project actually needs. I won't pretend to know something I don't, and I won't talk you into AI when a SQL query would do the job. If you're building something AI-powered and want someone who can also handle the unglamorous parts (the auth, the deployment, the schema, the UI that doesn't make users cry), let's talk.

I'm a web developer with extensive experience in building high quality sites. My experiences range from building responsive sites that work well cross-browser and on mobile to building sites that integrate with 3rd party systems like Salesforce. Most of my projects leverage tools like Drupal or Wordpress. I like working on projects with a team that cares about creating useful tools and usable interfaces. I am a good communicator and always strive to delight. It's important to me to build long term relationships with clients, so I'm primarily looking for long term projects. I am an excellent troubleshooter with the ability to make things work. I'm flexible with my working hours and am happy to work closely with any existing freelancers you work with. I look forward to hearing from you!

I help teams turn AI ideas into production-ready systems: RAG applications, AI agents, LLM-powered workflows, enterprise knowledge assistants, and AWS-native GenAI platforms that connect to real data, APIs, security controls, and cloud infrastructure. My advantage is the combination most AI projects need but many freelancers miss: enterprise application architecture plus modern Generative AI engineering. I can help you move from business problem to architecture, prototype, integrations, AWS deployment, observability, security, and cost control. WHAT I CAN BUILD - Enterprise RAG systems for company documents, policies, SOPs, technical content, and knowledge bases - AI agents that use tools, call business APIs, follow rules, and return structured outputs - AWS GenAI architectures using Amazon Bedrock, serverless services, APIs, storage, queues, containers, and monitoring - LLM integrations with OpenAI, Anthropic Claude, Gemini, Amazon Bedrock, or similar providers - AI automation workflows for operations, support, internal knowledge, document processing, and application modernization - Architecture reviews for AI systems that are unreliable, expensive, hard to scale, or not ready for production AI / GENAI FOCUS RAG, advanced RAG patterns, embeddings, vector search, semantic search, reranking, knowledge graph + RAG design, AI agents, multi-step workflows, tool calling, structured outputs, prompt engineering, LLM evaluation, hallucination reduction, and production AI architecture. ENTERPRISE / AWS BACKGROUND My professional foundation is enterprise-scale application and cloud architecture: AWS, serverless architecture, microservices, Java, APIs, CI/CD, DevOps, infrastructure automation, observability, security, software supply chain, Nexus Repository, Sonar, Amazon ECR, SBOM, and production reliability. That matters because real AI applications are not just prompts. They need data pipelines, authentication, authorization, API boundaries, monitoring, deployment strategy, cost controls, and maintainable architecture. EXAMPLE PROBLEMS I CAN HELP SOLVE - "We need a RAG assistant that answers from our documents with citations." - "We have an AI prototype, but we need a production architecture our team can actually operate." - "We need an agent that connects to our internal systems instead of just chatting." - "Our chatbot gives confident wrong answers and we need retrieval/evaluation fixed." - "We want to use Amazon Bedrock but need help designing the architecture and integration path." - "Our LLM usage is becoming expensive and we need cost, latency, and reliability improvements." TECH STACK AI/LLM: Amazon Bedrock, OpenAI, Claude, Gemini, LangChain, LangGraph, LlamaIndex, RAG, embeddings, vector databases, structured outputs, tool calling, LLM evaluation AWS/Backend: AWS Lambda, API Gateway, ECS/ECR, S3, IAM, CloudWatch, serverless architecture, microservices, REST APIs, Java, Python/FastAPI, CI/CD Data/Search: PostgreSQL/pgvector, OpenSearch, Pinecone, Qdrant, semantic search, knowledge graphs, document ingestion, metadata filtering HOW I WORK 1. Clarify the business workflow, users, data, and success criteria 2. Choose the right pattern: RAG, agent, workflow automation, search, or hybrid architecture 3. Build a focused prototype with measurable quality checks 4. Add security, deployment, observability, cost controls, and handoff documentation 5. Improve accuracy, latency, reliability, and maintainability before scaling If you need someone who can think beyond a demo and design the AI system as part of a real production platform, I can help.

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 help companies move, process, and use their data on AWS — from event-driven ETL pipelines to RAG-powered AI applications. For the past 4+ years I've built exactly that at the U.S. Securities and Exchange Commission, handling high-volume financial data. THREE THINGS I DO 1. DATA ENGINEERING — Design and build ETL/ELT pipelines with Apache Airflow, PySpark, AWS Glue, and Redshift/Iceberg. Batch or event-driven, greenfield builds or rescuing pipelines that keep breaking. 2. CLOUD ARCHITECTURE (AWS) — Architect serverless and containerized systems with Lambda, ECS, S3, and DataSync, all as infrastructure-as-code (AWS CDK, CloudFormation). Migrate legacy on-prem workloads to AWS with CI/CD from day one. 3. AI & LLM APPLICATIONS — Build RAG systems with vector search (Qdrant), LLM-powered document analysis, and AI features shipped inside real products (Python, Next.js, OpenAI API). RESULTS I'VE DELIVERED • Cut data availability from ~1 hour to minutes with event-driven AWS pipelines (SEC) • Reduced deployment cycles from 9 weeks to 4 by automating CI/CD for AWS Glue ETL jobs (SEC) • Built a private RAG document-Q&A system over internal docs — semantic search with no data leaving the org • Saved 75 analyst-hours per week by automating manual data workflows (Comcast) TECH STACK • Languages: Python, SQL, TypeScript/JavaScript, R, Golang • Data Engineering: Apache Airflow, PySpark, AWS Glue, Pandas, NumPy, Alteryx • AWS Cloud: S3, Lambda, ECS, EC2, Athena, Redshift, Iceberg, DataSync, RDS/Aurora, DynamoDB, SNS, CDK, CloudFormation, SAM, LocalStack, CloudWatch • AI / LLM: LLM API(Anthropic, Gemini, OpenAI), Vector DB, RAG pipelines, AI-assisted development with Claude Code & Cursor • Databases: PostgreSQL, MySQL, Redshift, MongoDB, Neo4j, DynamoDB, Supabase • Web & APIs: React, Next.js, Node.js, FastAPI, Flask, Prisma • DevOps: Docker, GitHub Actions, Bamboo, Splunk, Jupyter CERTIFICATIONS • AWS Certified Solutions Architect • AWS Certified Data Engineer HOW I WORK Clear communication, tested code, and documentation your team can actually maintain. Everything I build is infrastructure-as-code — reproducible in your environment, no black boxes, no key-person risk. Tell me about your data stack, your cloud setup, or the AI feature you want to ship — I'll reply with a concrete plan for how I'd build it.