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I’m a process-focused program manager, because well-formed processes minimize friction for teams to deliver and leaders to decide. Most of my career has been building intake, estimation, planning, and reporting processes, and getting people to adopt them.

I trained as a mechanical engineer, worked in technical writing at Morgan Stanley and State Street, and later moved from delivery management into enterprise program leadership at Booz Allen Hamilton. I can take an engineering constraint to a sales team, or a business priority to an engineering team, and get both sides to buy in.

• At Booz Allen, as Deputy Program Manager of an $18 million, 160-person Scaled Agile program, I twice realigned reporting lines for 100+ staff, and the program still met 100% of its commitments on time.
• Earlier, I launched a SaaS developer portal to 650 users in week 1 and 3,500 of a 5,000-user target in year 1. I also co-organized an internal hackathon where all 15 teams built working applications on the portal in under 12 hours. It was the best team I’ve been part of.
• I built a supportive PMO from nothing to cover 4 product-innovation programs. Leadership made my Jira setup the default for 500 internal-project users, and teams still used it in 2026.
• At State Street, I introduced a documentation system for 115 financial instrument models that reached 90% usage within 6 months; translating 15 financial engineers’ work into plain language for 60 non-technical salespeople cut internal consultations 30%.
• At Anatta, I built the company’s first intake system, which leadership adopted as standard process, and wrote its first Agile estimation guidebook.

I’m a servant leader at heart. Some of my proudest moments were seeing people I’d developed earn accolades; in 7 years of direct people management, 75%+ of my reports earned promotions, and 3 became my peers.

I think of AI as a delivery acceleration tool that needs tight constraints and human approval gates. It can save a lot of time, but it’s prone to grievous errors, so it has to be supervised until it’s accurate, not just fast. At Booz Allen, I promoted responsible AI practices across 20+ teams, including human review, output ownership, and data security. At Anatta, I built sandboxed AI agents that generated daily client stakeholder summaries and drafted biweekly executive steering-deck updates, saving 2+ hours a week and 6+ hours per refresh. I reviewed every output before anyone else saw it.

I measure twice and cut once, because a better way of working only matters if people actually use it.