Resume

Shawn Brinkley

AI/ML Engineering Leadership
804-338-3181 brinkley.shawn@gmail.com Richmond, VA linkedin.com/in/shawn-brinkley github.com/Brinkv3
6 → 30+
ML org built at Capital One
Zero
Attrition, three years running
$2T+
Transactions via Fed CASH
25+
Years in regulated industries
Professional Summary

Technology leader with more than 25 years of experience building, leading, and scaling engineering organizations in regulated environments. AI/ML leadership including building a machine learning engineering organization from 6 to 30+ at Capital One, leading 4–6 ML programs simultaneously across the enterprise, and maintaining zero attrition for 3 years through a tech forward but people first leadership approach.

Proven ability to manage through people, empowering managers and working through individual contributors and cross-functional partners to deliver production AI/ML solutions. Equally credible with engineering teams, risk officers, and executive leadership. Currently operating as an independent consultant focused on AI strategy, data architecture, and enterprise delivery, while maintaining hands-on proficiency in agentic AI, generative AI, retrieval systems, and AI governance.

Areas of Expertise
AI/ML Strategy, Agentic AI, Generative AI
Team Leadership, Coaching, Mentoring
Managing Through People, Org Building
AI Governance, Model Risk, Responsible AI
Enterprise Architecture, Data Platforms
Cross-Functional Stakeholder Partnership
Program Strategy, Portfolio Management
Delivery Excellence, Agile/Lean Practices
Career Experience
June 2026 – Present
Richmond, VA

Founder

Carter Brinkley Consulting LLC

Independent technical consulting practice focused on AI strategy, data architecture, and enterprise delivery in regulated industries.

  • Lead data and application integration audits for clients, interviewing application teams across enterprise platforms, mapping data flows, identifying architectural patterns, and producing current-state assessments with future-state recommendations.
  • Strategic planning for Fortune 500 CTO delivering Organizational Op Model and multi-year Tech Strategy, including AI enablement and advancement. Partnered with Tech PMO to establish metrics-driven tracking and visibility across the portfolio.
  • Built and published five production-patterned AI systems covering RAG with multi-agent orchestration, document intelligence, agentic workflow automation, MCP-based tool interoperability, and provider-agnostic model abstraction. All systems built with evaluation from Day 1, AI governance as architecture, and no framework dependency.
July 2025 – June 2026
Richmond, VA

Head of Engineering

SingleStone Consulting
  • As part of the SLT, led the engineering practice for a technology consulting firm, responsible for 25–30 ML/AI, data, and software engineers across client delivery engagements. Defined the new talent bar for the AI-driven market and recruited to match.
  • Oversaw engineering quality, staffing, delivery, and architectural direction across multiple concurrent client engagements in regulated industries. Partnered with sales and client stakeholders to scope and staff technical engagements.
  • Direct client work including ML models, operating models, data audits, and tech strategies, plus most Principal-level C-Suite consulting for tech-forward engagements.
  • Partnered with the Head of AI to train engineers and non-technical staff on leveraging AI in client and day-to-day work. Created an AI Studio sandbox for PoC and IP development.
  • Coordinated multiple AI dev hackathons including Hack for RVA, winning the Thriving Neighborhoods pillar for SIMBY, an AI and community-driven engagement app built on real city development data.
Sept 2024 – June 2025
Bethesda, MD (Remote)

Technical Program Manager (Consultant)

Marriott HQ

Contracted to support a VP-led initiative modernizing enterprise infrastructure, network, and digital traffic flow in preparation for AI/ML product development.

  • Advised VP and C-Suite on targeted infrastructure improvements delivering the greatest operational and financial lift.
  • Coordinated across enterprise architecture, network, and all digital customer-facing applications to improve efficiency, reduce outages, and strengthen stability.
  • Identified enhancements — global routing, edge caching, additional production locations, service mesh — estimated at $500M to $1B in annualized savings.
2019 – Aug 2024
Richmond, VA
Promoted from Senior Manager (2019–2021) to Director (2021–2024)

Director of Innovation and Applied ML

Capital One

Recruited to expand in-house AI/ML consulting and lead the Center for Machine Learning in transitioning ideas from proof-of-concept to enterprise-wide solutions. Built and led a nationally distributed, cross-functional team implementing AI/ML across Anti-Money Laundering, Fraud Detection, Corporate Strategy, Card, and Credit Risk Assessment.

Team Building and Leadership
  • Built the ML Engineering organization from 6 to 30+ engineers, fostering a culture that achieved zero attrition for 3 years, a 100% leadership approval rating, and 88% staff engagement.
  • Managed 4 Senior Managers as direct reports, running 4–6 ML programs simultaneously with a mandate to enable machine learning across nearly every department in the enterprise.
  • Held dotted-line responsibility for data scientists, project, program, and product managers across delivery and research. Total organizational sphere of 35–40+ people.
Strategy and Delivery
  • Spearheaded development of 15+ MVP solutions in FinTech and ML, focused on reusability and responsible technology for lines of business and VP-level stakeholders.
  • Drove the organizational shift from bespoke solution design to an enterprise-wide model that streamlined project transitions and change management.
  • Partnered with platform teams to onboard ML services to enterprise readiness, bridging proof-of-concept to production deployment.
  • Served as SME for compliance with global, federal, state, and internal regulations relating to FinTech, ML, and responsible use of data. Built deliverables that survived Model Risk Governance review.
Notable Solutions Delivered
Lustr
Model explainability and monitoring solution impacting 50,000+ employees, enabling interpretation of model outputs and providing monitoring insights in compliance with industry regulations.
BESTie
Data pipeline reengineering that reduced multi-million-dollar recurring data purchase dependencies and improved data quality.
Anomoleas
Enterprise-grade data anomaly detection solution improving identification of key risk factors during model monitoring.
2008 – 2018
Richmond, VA

Information Technology Manager

Federal Reserve Bank of Richmond

Promoted to oversee IT operations, ensuring compliance with federally mandated technical regulations. Led cross-functional IT support teams including 8 direct reports and 20 project team members across multiple locations while owning a $20 million portfolio.

  • Led the Cash Policy team for the largest software development program in the Federal Reserve's history, directing a global Agile development team facilitating more than $2 trillion in safe, secure transactions as part of the CASH application.
  • Deployed a concierge support model and in-house DevOps solution, generating a new business line across multiple districts and establishing nationwide development practices.
  • Administered independent project budgets between $2M and $5M, including rolling out the organization's largest software suite as a member of the project leadership team.
  • Coordinated end-to-end server migration resulting in over $250,000 in annual cost savings.
  • Executed initiatives in secure coding, test automation, and threat management, ensuring compliance with system standards.
2000 – 2008
Richmond, VA

Tech Lead, IT and Application Development

Federal Reserve Bank of Richmond

Navigated early adoption of critical systems, mobile technologies, and remote work infrastructure before transitioning to national-scale software development, leading testing, development, and orchestration of engineering teams.

Technical Portfolio

What I've Built

Five public repositories demonstrating hands-on AI/ML engineering alongside leadership experience. All systems include evaluation from Day 1, no framework dependency, and AI governance as a first-class architectural concern.

rag-pipeline
Multi-agent RAG with retrieval, grounded generation, dual-mode evaluation, and built-in governance: prompt injection detection, PII redaction, autonomy tiers, token budgets, structured audit logging.
View on GitHub →
97% retrieval
99% faithfulness
doc-intelligence
Schema-driven document classification, structured field extraction, validation, and cross-document analysis. Adding a new document type means adding a JSON file, not writing new code.
View on GitHub →
100% classification
100% extraction
consulting-mcp-server
MCP server exposing both pipelines as 8 tools consumable by any MCP-compatible AI client. Protocol-level interoperability tying multiple AI capabilities into a single composable surface.
View on GitHub →
8 tools
25 tests
agentic-audit
End-to-end agentic workflow automating the consulting data audit discovery process. Interview question generation through answer synthesis with factual vs anecdotal classification.
View on GitHub →
6 agents
full pipeline
llm-adapter
Provider-agnostic LLM abstraction layer. Swap providers by changing one line in a config file. Supports Anthropic, OpenAI, Azure, Bedrock, and local models.
View on GitHub →
5 providers
pip-installable
Credentials

Education and Certifications

Executive Certificate, Machine Learning in Business
Massachusetts Institute of Technology (MIT), Cambridge, MA
BS, Computer and Information Systems (Information Security)
Strayer University, Washington, DC
Project Management Professional (PMP)
Project Management Institute
ITIL Certified  ·  CMMI Level 3
IT Service Management · Department Certification

Let's talk.

Richmond, VA · Available for consulting engagements, advisory work, and leadership roles.