{ "$schema": "https://raw.githubusercontent.com/jsonresume/resume-schema/master/schema.json", "basics": { "name": "Daniel Plas Rivera", "label": "Lead Software Engineer, AI/ML & LLM Platforms", "email": "plasx1987@gmail.com", "phone": "(212) 470-2431", "url": "https://morphus56k.com", "summary": "Lead software engineer with 15+ years shipping production systems, now focused on AI/ML platforms: LLM orchestration and agent tooling (Model Context Protocol), retrieval-augmented generation, explainable-AI citation grounding, and fine-tuned transformer models. I design multi-provider LLM gateways, vision-based document-intelligence pipelines, and hierarchical ML classifiers, then ship them end to end—from FastAPI backends to modern React/TypeScript front ends—on AWS with rigorous evals, streaming APIs, and CI/CD. Expert in modern Python, TypeScript/React, FastAPI, PyTorch/HuggingFace, and cloud infrastructure.", "location": { "city": "New York", "region": "New York", "countryCode": "US" }, "profiles": [ { "network": "LinkedIn", "username": "plasnyc", "url": "https://www.linkedin.com/in/plasnyc" }, { "network": "GitHub", "username": "plasx", "url": "https://github.com/plasx" }, { "network": "Twitter", "username": "plasx", "url": "https://twitter.com/plasx" } ] }, "work": [ { "name": "McKinsey & Company", "position": "Lead Software Architect", "url": "https://www.mckinsey.com/", "startDate": "2023-01-01", "summary": "Lead architect for GenAI/LLM products and AI platform engineering across 25+ teams. Own end-to-end AI systems—LLM agent tooling, multi-provider model gateways, document intelligence, and ML classification—delivered as streaming APIs on AWS with production evals and CI/CD.", "highlights": [ "Built a Model Context Protocol (MCP) server exposing 75+ agent tools behind a tool-RAG discovery layer (list/search/describe/call) that reduces tool-selection errors for LLM agents; added a sandboxed code-execution mode for multi-tool composition, durable async job orchestration with idempotency, and confirm-guards on destructive operations", "Architected a multi-provider LLM gateway unifying Anthropic, OpenAI/Azure, Google/Vertex, and AWS Bedrock behind a single model-facade with capability gating, NDJSON/SSE token streaming, and provider-native citation grounding", "Engineered a vision-LLM document-intelligence pipeline for PDF extraction with page-anchored citations, metadata detection, and cancellable async batch jobs, converting unstructured reports into auditable, source-linked insights", "Delivered an Explainable AI layer with evidence-first trust scoring, citation provenance, and W3C SHACL / JSON-LD ontology validation so every AI-generated claim traces back to a cited source", "Designed a hierarchical transformer classifier (DeBERTa/RoBERTa via HuggingFace) that maps records into a 4-level, 137-path taxonomy; raised deepest-level accuracy from ~4% to 77%+ using class-weighted and focal loss with branch oversampling", "Built the classifier's MLOps end-to-end: GPU fine-tuning on AWS SageMaker triggered from CI, FastAPI serving on ECS Fargate, and EFS-versioned model artifacts with symlink-based rollout and graceful degradation", "Created offline evaluation harnesses comparing frontier vs. baseline models on latency, token cost, and output quality—with automated hallucination and quality scoring across multiple dimensions—to inform production model selection", "Migrated embeddings storage from ChromaDB to PostgreSQL/pgvector, achieving sub-100ms similarity search on 100K+ vectors via proper indexing and connection pooling", "Led a thin-client decoupling that moved all LLM/SDK work behind the FastAPI gateway (feature-flagged and guardrail-enforced), extending the API surface to ~120 endpoints across versioned APIs with async batch jobs and SSE progress streaming", "Built a production React 19 / TypeScript / Vite front end (Tailwind CSS + shadcn/ui, Zustand state) featuring an SSE streaming chat interface with inline charts and click-to-source citation markers, elevating an analyst tool from prototype to client-ready web application", "Added constrained LLM tool-calling for ontology-validated data queries and in-chat chart generation/editing, plus web-search-grounded autofill with per-field confidence scoring and a human accept/reject review flow", "Shipped multi-format deliverable export—native editable PowerPoint charts, filled Excel workbooks, and self-contained interactive HTML reports—via async job orchestration with human-in-the-loop approval before export", "Implemented real-time multi-currency financial normalization and reactive data transformations powering interactive analytics tables and human-in-the-loop validation of AI-generated insights", "Designed AWS document-repository and knowledge-base infrastructure with Terraform—KMS encryption, event-driven ingestion, and audit logging for compliance", "Drove engineering quality with a large automated test suite (unit, integration, BDD, and Playwright E2E), SonarQube gates, and Release Please monorepo versioning" ], "keywords": ["Python", "TypeScript", "FastAPI", "React", "Vite", "Tailwind CSS", "shadcn/ui", "PyTorch", "HuggingFace Transformers", "scikit-learn", "LangChain/LangGraph", "Model Context Protocol (FastMCP)", "Anthropic/OpenAI/Google/Bedrock APIs", "PostgreSQL/pgvector", "Redis/Celery", "AWS (SageMaker, ECS/Fargate, Bedrock, S3, KMS, Lambda)", "Terraform", "Docker", "Kubernetes", "GitHub Actions", "SonarQube"] }, { "name": "McKinsey & Company", "position": "Lead Senior Software Engineer", "url": "https://www.mckinsey.com/", "startDate": "2020-05-29", "endDate": "2023-01-01", "summary": "Led data engineering for multiple analytics teams, delivering end-to-end pipelines across 10+ enterprise data sources (Slack, Zoom, Microsoft Teams, SharePoint, Outlook, Box, VPN monitoring) and processing hundreds of millions of API calls daily into Snowflake.", "highlights": [ "Architected a production data platform with 10+ AWS Glue pipelines using Pydantic for schema mapping and compliance, cutting API calls from 16.5M to sub-million daily while preserving data completeness", "Reduced AWS expenditure by 99.6% (over $47K/year) by re-architecting serverless workloads onto AWS Kinesis for high-throughput streaming", "Deployed a VPN-monitoring streaming solution on a full AWS stack: API Gateway with WAF IP whitelisting, Lambda Authorizers, KMS-encrypted S3, and Kinesis Stream/Firehose for cross-channel analytics", "Led a legacy webhook migration, architecting webhook validation with secure handshakes via Lambda Authorizers to recover broken data streams and reduce rate-limit failures at enterprise scale", "Engineered Snowflake automation (snowpipes, streams, tasks, merge/upsert) for 200-day backfills, orchestrated by AWS Step Functions for dependency-based execution", "Raised unit-test coverage from 0% to 80% across 10+ Glue pipelines, meeting enterprise quality gates", "Implemented repository security scanning (SAST, secret scanning, SCA, IaC) with pre-commit hooks across 100+ pipelines, and remediated 10+ critical vulnerabilities (EC2 IMDSv2, S3 CMK enforcement, WAF rules, SSH restrictions, CloudFormation hardening)", "Built event-tracking pipelines with Terraform and Snowflake cross-account storage integrations (DEV/TEST/PROD), and upgraded AWS Glue 4.0 → 5.0 for a modernized Spark runtime" ], "keywords": ["Python", "Pydantic", "AWS Glue", "Spark", "Snowflake", "AWS (Lambda, Kinesis, Firehose, S3, KMS, Step Functions, API Gateway, WAF)", "Terraform", "Microsoft Graph API", "Docker", "Kubernetes", "GoCD", "SonarQube"] }, { "name": "Price Waterhouse Coopers", "position": "Developer - Contractor", "startDate": "2019-12-04", "endDate": "2020-03-20", "summary": "Built the backend for a data-risk analysis platform that detects and assesses security risks of client-provided data, consumed by a React SPA.", "keywords": ["Docker", "Django 3", "Python 3", "Graphene", "GraphQL", "DRF", "React"] }, { "name": "Capital One", "position": "Master Software Engineer - Contractor", "startDate": "2019-05-13", "endDate": "2019-08-22", "summary": "Re-architected a Credit Risk Rating platform enabling risk rating of customers and facilities to support credit-approval decisions and ongoing portfolio management; dockerized microservices including a probability-of-default model service.", "keywords": ["Python", "Flask", "SQLAlchemy", "Oracle", "Postgres", "Jenkins", "Docker", "Artifactory"] }, { "name": "Cox Automotive", "position": "Sr. Python Full Stack Engineer - Contractor", "startDate": "2018-08-08", "endDate": "2019-03-01", "summary": "Full-stack Python engineer in Finance & Insurance: Docker container infrastructure, CI/CD pipelines, SOA appliances; performance analysis via New Relic and Splunk.", "keywords": ["Python", "Django", "Flask", "Celery", "React", "Redis", "Jenkins", "Docker", "IBM DataPower", "Splunk", "New Relic"] }, { "name": "Price Waterhouse Coopers", "position": "Developer - Contractor", "startDate": "2017-12-04", "endDate": "2018-07-02", "summary": "Integrated VPN technologies into an internal tax-audit platform on Azure, launching VPN containers on demand via PaaS; refactored Python applications for SnapLogic pipelines.", "keywords": ["Python 3", "Celery", "Redis", "React", "Django", "Docker", "Azure", "IPsec/VPN", "SnapLogic", "AWS"] }, { "name": "Bank of America", "position": "Application Architect V - Contractor", "startDate": "2017-07-10", "endDate": "2017-10-17", "summary": "Defined target-state cloud architecture, supporting organization model, and platform roadmap; REST APIs, POCs, and feasibility studies guiding business and technology decisions.", "keywords": ["Python 3", "Microsoft Azure", "Terraform", "Packer", "Flask", "MongoDB", "TDD", "Jenkins"] }, { "name": "Columbia University", "position": "Application Systems Developer - Python/PHP", "startDate": "2016-04-18", "endDate": "2017-07-06", "summary": "Transitioned the University to a Python stack while maintaining legacy compatibility; full-stack applications and REST APIs with role-based access control; designed the server/infrastructure flow.", "keywords": ["Python 3", "Flask", "Oracle", "Apache/mod_wsgi", "Vagrant", "Docker", "Jenkins", "OAuth1/OAuth2", "LTI", "Node.js"] }, { "name": "Brainy Maps", "position": "President (Founder)", "startDate": "2016-06-01", "endDate": "2017-11-11", "summary": "Founded a location-based app delivering real-time local information; React/React Native front end and RESTful CRUD backend with Google Maps integration (iOS focus)." }, { "name": "Thinkful", "position": "Python & Front-end Web Development Mentor", "startDate": "2015-06-18", "endDate": "2016-04-06", "summary": "Mentored aspiring developers through a project-based Python and web-development curriculum via weekly one-on-one sessions and code reviews." }, { "name": "Work-Bench", "position": "Part Time Developer", "startDate": "2015-11-12", "endDate": "2016-07-01", "summary": "Responsive revamp of the careers page with an Indeed-API job scraper and sortable, filterable job feed (Ruby, Middleman, JavaScript, Bootstrap)." }, { "name": "Basics Plus", "position": "Lead Full Stack Developer", "startDate": "2015-01-15", "endDate": "2015-06-01", "summary": "Built and maintained e-commerce systems for a NYC houseware/hardware retail chain and subsidiaries; led the dev/SEO team and partnered with Google strategists to grow sales and search ranking (Magento, MySQL, PHP)." }, { "name": "New York City College Of Technology", "position": "College Laboratory Technician", "startDate": "2014-01-01", "endDate": "2015-01-01", "summary": "Assisted professors in instructing courses on code, video, and hardware projects (Arduino, Raspberry Pi, MakerBot) and demoed emerging technologies." }, { "name": "The K.I.S. Foundation, Inc.", "position": "Part Time Full Stack PHP Developer", "startDate": "2010-06-01", "endDate": "2017-09-18", "summary": "Built and maintained the nonprofit's web presence to raise sickle-cell-disease awareness, migrating Joomla to a customized WordPress theme." }, { "name": "The Next Phase Entertainment, LLC.", "position": "Part Time Full Stack PHP Developer", "startDate": "2009-06-01", "endDate": "2013-12-30", "summary": "Designed and developed websites for multiple artists under the label (WordPress, PHP, jQuery, Bootstrap)." } ], "projects": [ { "name": "Memorial fighting-game AI (alanmargolies88)", "description": "Behavioral clone of a deceased Fightcade player: VQ-BeT tokenized policy (16-frame action chunks, 256-entry codebook) trained on 7,300+ replays, fine-tuned with style-constrained PPO on Apple MLX. 266-dim RAM-level perception reverse-engineered from CPS-2 memory. ~34 verified arXiv papers folded into the design.", "url": "https://morphus56k.com/blog/memorial-bot-complete-arc", "keywords": ["reinforcement learning", "behavioral cloning", "VQ-VAE", "PPO", "MLX", "emulation"] }, { "name": "CPS-2 reverse engineering program", "description": "Multi-year self-directed research: 68000 disassembly, custom FBNeo emulator cores breaking the 32MB graphics cap to 64MB (pixel-proven), cross-architecture audio injection via hand-assembled Z80, new playable characters ported between games.", "url": "https://morphus56k.com/blog/selected-work", "keywords": ["reverse engineering", "68000 assembly", "Z80", "emulation", "binary analysis"] }, { "name": "Arcade1Up online protocol RE", "description": "Commercial cabinet netplay stack reverse-engineered from ARM32 disassembly: KCP transport, witness spectate streams, GGPO rollback, cross-architecture state-resume analysis.", "url": "https://morphus56k.com/blog/arcade1up-online-reverse-engineering", "keywords": ["network protocols", "disassembly", "GGPO", "emulation"] } ], "skills": [ { "name": "Languages", "keywords": ["Python", "TypeScript", "SQL", "JavaScript", "Bash"] }, { "name": "Frontend", "keywords": ["React 19", "Vite", "Tailwind CSS", "shadcn/ui (Radix)", "Zustand", "React Router", "Recharts", "SSE streaming UI", "Vitest"] }, { "name": "AI/ML & LLM", "keywords": ["LLM orchestration", "AI agents & tool use", "Model Context Protocol (MCP)", "Retrieval-Augmented Generation (RAG)", "Fine-tuning", "PyTorch", "HuggingFace Transformers", "scikit-learn", "LangChain / LangGraph", "Prompt engineering", "Model evaluation (evals)", "Explainable AI (citations & grounding)", "pgvector embeddings"] }, { "name": "LLM Providers", "keywords": ["Anthropic Claude", "OpenAI / Azure OpenAI", "Google Gemini / Vertex AI", "AWS Bedrock", "Perplexity"] }, { "name": "Backend & Streaming", "keywords": ["FastAPI", "asyncio", "SSE / NDJSON streaming", "Celery + Redis", "SQLAlchemy", "Alembic", "Pydantic", "REST APIs"] }, { "name": "Cloud & Infrastructure", "keywords": ["AWS (SageMaker, ECS/Fargate, Bedrock, S3, KMS, Lambda, Kinesis)", "Terraform", "Docker", "Kubernetes", "GitHub Actions", "CI/CD", "SonarQube"] }, { "name": "Data", "keywords": ["Snowflake", "PostgreSQL", "Spark / AWS Glue", "Kinesis / Kafka", "Pandas", "Plotly"] } ], "education": [ { "institution": "Hunter College", "area": "Emerging Media", "endDate": "2014-05-24" }, { "institution": "New York City College of Technology", "area": "Emerging Media Technologies", "endDate": "2013-05-24" }, { "institution": "Borough of Manhattan Community College", "area": "Multimedia Programming & Design", "endDate": "2010-12-15" }, { "institution": "School of Cooperative Technical Education", "area": "Cisco Networking and CompTIA PC Repair Training", "endDate": "2005-01-05" } ], "certificates": [{ "name": "AWS Certified Cloud Practitioner", "issuer": "Amazon Web Services" }], "awards": [ { "title": "AngelHack 2016 Manhattan", "date": "2016-06-04", "awarder": "AngelHack", "summary": "Winner of the Grand Prize (Hackcelerator) and Best Use of Amazon Web Services. New York Minute: pocket companion calculating the fastest, cheapest way around NYC comparing ride-share and public transit. AWS (Elastic Beanstalk, EC2, Route 53, S3), Amazon Alexa, Esri ArcGIS." }, { "title": "Hack NYU Hackathon", "date": "2014-05-06", "awarder": "NYU", "summary": "MVP Winner. SudoLove connects participants, sponsors and mentors for global hackathons via an app." } ], "references": [ { "name": "Latonia Robinson, Dir. of Operations, The K.I.S. Foundation", "reference": "Daniel is an absolute joy to work with and continues to impress us with his technical skill sets. Whenever we have a problem with our website, he always has the answer or recommendations for improvement. Daniel follows direction well, he's always aware of the latest programs or trends, he works well with deadlines, he's able to communicate effectively, he's super reliable, and his experience is absolutely priceless." }, { "name": "Antonio Riccardi, Web Engineer at Basics Plus", "reference": "Daniel is one of the best developers we know. His speed and ability to conquer any challenge thrown at him helped us recover our online presence. He led our team here through rigorous challenges with unique solutions each time always getting the job done before the deadlines." } ], "meta": { "canonical": "https://github.com/plasx/jsonresume/blob/master/resume.json", "version": "v2.0.0", "lastModified": "2026-07-05" } }