In this episode, Mehmet Gonullu sits down with Mary Moore-Simmons, VP of Engineering at Keebo AI, to unpack what it really takes to scale high-performing engineering teams in today’s AI-powered environment. From DevOps and ML Ops to building team culture that lasts, Mary shares hard-won insights from over a decade in engineering leadership across startups and high-growth tech companies.

This is a must-listen for founders, CTOs, and venture investors seeking clarity on where engineering, AI, and culture intersect.

🔑 Key Takeaways

• The shift from traditional DevOps to ML Ops and its impact on team structure

• Why data engineering is no longer optional, even for product-focused engineers

• How to balance velocity with sustainable engineering culture

• The real difference between a CTO and a VP of Engineering

• Why culture must be owned—and modeled—by the CEO to scale

• How Mary mentors future leaders through transparency and structure

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📘 What You’ll Learn

• The traits Mary looks for when hiring for early-stage engineering teams

• How to scope early features in a fast-moving startup environment

• Strategies to shield your team from “firefighting” and maintain focus

• The importance of infrastructure automation in the age of AI

• Mary’s thoughts on whether company culture can truly scale

👤 About the Guest

Mary Moore Simmons is the VP of Engineering at Keebo.ai, where she has been instrumental in shaping the company's innovative approach to data warehouse optimization. A seasoned engineering leader with 10+ years in software, her background includes Director of Engineering at Github and Zcash as well as VP of Engineering at AgentSync. She focuses on building high-performing teams that sustain a healthy culture and growth mindset. She is passionate about authentic and transparent leadership, and building a culture where people can bring their authentic selves to work, where DEIB is table stakes.

https://www.linkedin.com/in/mmooresimmons

http://keebo.ai/

https://github.com/mmsthepizzathief

Episode Highlights & Timestamps

00:01 – Mary’s journey: from chemical engineer to VP of Engineering

03:20 – What Keebo AI does and how they optimize Snowflake & Databricks

05:10 – The evolving intersection of software and data engineering

07:00 – Why Mary prioritizes hiring with data and ML experience

08:30 – DevOps, ML Ops, and keeping engineers happy and efficient

10:50 – The CTO vs VP of Engineering: What really separates the two

13:30 – Balancing velocity vs long-term stability in startup engineering

18:45 – How Mary shields her team from noise and burnout

22:00 – The traits Mary looks for when hiring

23:30 – Authentic and transparent leadership in practice

25:30 – Does culture scale? What Mary has seen work

28:30 – What goes wrong when companies scale too fast

33:00 – Coaching future leaders and creating career ladders

37:00 – Tools, books, and blog posts Mary recommends

38:00 – AI, automation, and what tech excites Mary today

40:00 – Where to connect with Mary