# Brown Brothers Harriman — AI Technical Project Manager

- Generated: 2026-09-18 10:04:40 AM EDT
- Original/canonical posting: https://www.bbh.com/us/en/careers.html
- Provider: User-provided JD text
- Posted: Not disclosed
- Elapsed since posting: represented by the provider's relative posting label and approximate Eastern timestamp when available
- Applicants: Not disclosed
- Work model/location: Not disclosed in the supplied JD; exact public posting URL was not provided or found
- Compensation: Not disclosed; Project Manager title does not qualify for the undisclosed-compensation exception
- Travel: Not disclosed
- Positioning track: Technical manager
- Fit outcome: FAIL — 96%

## Direct-match strengths

AI program delivery, GenAI and agentic platforms, project planning, budgets, risk and dependency management, developer productivity, legacy modernization, enterprise architecture, cloud, cybersecurity, governance, Responsible AI, regulated financial services, executive reporting, adoption, KPIs, cost controls, and ROI.

## Hard or material gaps

Formal fit-gate FAIL because compensation and work model are undisclosed for a non-qualifying title. Keith explicitly requested generation despite those policy caveats. PMP is not documented; Azure Foundry and GitHub Copilot are unsupported, while comparable AWS, Codex, and enterprise AI-platform evidence is direct.

## Evidence map

1. 10+ years project/program management (weight 3, evidence 3/3) — Twenty-nine years of project management plus repeated program, budget, risk, schedule, and delivery ownership.
2. 3+ years leading GenAI and ML initiatives (weight 3, evidence 3/3) — Production GenAI leadership since August 2023 plus long applied-ML and AWS AI/ML leadership.
3. GenAI, agents, AI SDLC, cloud, and developer productivity (weight 3, evidence 3/3) — Direct LLM, agent, RAG, MCP, AWS, CI/CD, evaluation, and Codex-enabled engineering evidence.
4. Cross-functional engineering, cyber, risk, compliance, and legal coordination (weight 3, evidence 3/3) — Direct regulated financial-services architecture, privacy, security, IAM, governance, and multidisciplinary delivery.
5. Schedules, budgets, resources, dependencies, and delivery risk (weight 3, evidence 3/3) — Direct planning, scheduling, budgets up to $900,000, resource leadership, risk, and status reporting.
6. AI governance and approved operating patterns (weight 3, evidence 3/3) — Direct Responsible AI, policy automation, bias, drift, oversight, security, monitoring, and auditability.
7. KPIs, adoption, productivity, cost, and ROI (weight 3, evidence 3/3) — Direct platform adoption, cycle-time, reliability, cost controls, business cases, KPIs, and quantified outcomes.
8. Preferred named tools and certifications (weight 1, evidence 1/3) — Codex, AWS, and certification-exam SME evidence are direct; PMP, Azure Foundry, and GitHub Copilot are not documented.
9. Eligible compensation and work model (weight 3, evidence 0/3) — Both are undisclosed; generation proceeds only because Keith explicitly requested it.

## Keyword diagnostic

Near-direct capability match across AI program delivery, technical coordination, governance, risk, adoption, developer productivity, metrics, and regulated financial-services technology; the formal failure is policy/metadata based rather than capability based.

## Full normalized job description

Brown Brothers Harriman is seeking an AI Technical Project Manager to lead adoption of AI-enabled products, platforms, and solutions across the organization. The role combines project-management discipline with technical understanding of AI/ML, data platforms, cloud infrastructure, and software engineering. Responsibilities include end-to-end delivery of Generative AI, Agentic AI, and machine-learning initiatives; scope, success metrics, milestones, schedules, budgets, resources, dependencies, risks, blockers, and concurrent workstreams; developer productivity and legacy-code modernization; stakeholder alignment across Software Development, Infrastructure, Cybersecurity, Legal, Compliance, Risk Management, Vendor Management, Architecture, Engineering, and business teams; governance standards, approved usage patterns, operating procedures, risk assessments, legal reviews, cybersecurity evaluations, regulatory requirements, integrations, security controls, and platform enhancements; technical design facilitation and architecture alignment; KPI, utilization, productivity, cost-optimization, ROI, executive-dashboard, and adoption reporting; and recommendations to expand, optimize, or retire AI capabilities. Required qualifications are 10+ years of project/program-management experience, 3+ years leading GenAI and ML initiatives, strong understanding of Generative AI, Agentic AI, AI SDLC, cloud platforms, developer-productivity tools, and enterprise architecture, plus cross-functional work with Engineering, Cyber, Risk, Compliance, and Legal and strong analytical, communication, and executive-presentation skills. Preferred qualifications include GitHub Copilot, Azure Foundry, Claude Code, or similar enterprise AI tools; technology adoption and change management; AI governance, software-development practices, and cloud platforms; PMP or equivalent; and a Generative AI certification covering LLMs, agents, RAG, prompting, enterprise architecture, security, and Responsible AI. Success measures include onboarding time, active users and platform adoption, productivity and efficiency gains, implementation of control requirements, and demonstrated business value, savings, and ROI.

## Artifact metadata

- Resume: https://bit.ly/4cSWbbd
- Cover letter: https://bit.ly/4j8Ekkn
- Validation: PASS — 2-page resume (934 words), 1-page cover letter (217 words); PDF geometry, bounds, annotations, links, and visual pages verified.
- Google Drive used: No

## Source caveat

The JD was supplied directly by Keith. No exact public posting URL was provided or found; the original-source link points to BBH's official careers hub.