Senior Director of Engineering, Core Product

The Opportunity

As a Senior Director of Engineering, Core Product at Coursedog, you'll own the day-to-day execution and engineering health of Coursedog's three core product clouds — Assessment, Curriculum, and Scheduling — so they ship reliably, hit their commitments, and defend the revenue base. You'll work closely with engineering managers, product leadership, and cross-functional partners to translate the roadmap into reliable, high-quality software. This is a delivery-and-execution leadership role — focused on building and running the products customers pay for today.

This role will be the single accountable leader for how core product engineering executes, week over week and quarter over quarter. You'll pioneer an AI-augmented development model where clear specifications unlock high-quality, AI-accelerated delivery. You'll be responsible for predictable shipping, quality, and reliability, and driving a step-change in engineering velocity through AI and spec-driven practices, while building a strong bench of engineering leaders in a fast-moving, mission-driven environment.

This role reports directly to the SVP, Software Engineering and collaborates cross-functionally. This role is well-suited for someone who operates with both strategic vision and operational rigor, takes ownership of hard problems, and is motivated by building systems and teams that scale sustainably.

If you're excited by the chance to lead a major engineering function, shape how a critical part of the product organization executes, and transform how an entire engineering org builds software through AI-augmented, spec-driven practices, this is an opportunity to have outsized impact at a high-growth company.

This position offers a competitive base salary between $175,000 - $200,000, based on experience and qualifications. The role also includes a performance-based variable compensation component, bringing total on-target earnings (OTE) to $210,000 - $250,000 when performance objectives are achieved.

What You'll Own:

• Lead the AI transformation into a spec-driven development org: Own the shift from ad-hoc coding to a spec-driven model where well-defined specifications drive design, implementation, review, and testing — and where AI tooling is used to accelerate delivery without eroding quality. Set the standard for how specs are written, versioned, and used as the contract between product intent and shipped code. Make AI-assisted development a durable competitive advantage across all three clouds, and raise the quality bar as AI-generated code volume grows.
• Lead through metrics: You run the org on data, not anecdote. Define the metrics that tell the truth about delivery, quality, and reliability; make them visible; and use them to drive decisions, expose risk early, and focus the teams. You model metric-driven leadership for your EMs and know when a number is a floor, a goal, or a distraction.
• Hold teams accountable: You are the single accountable leader for core product delivery, and you build that same accountability into every team. Set clear commitments and a clear definition of done, make ownership unambiguous, follow through on outcomes, and address underperformance directly and fairly. Commitments mean something on your teams.
• Build a continuous-improvement culture: Create an engineering culture that gets measurably better every quarter — where retros lead to change, standards rise over time, experimentation is safe, and improving the system is everyone's job. You partner with your engineering managers to make continuous improvement a habit, not an event.
• Multi-cloud engineering leadership: Set the standard for how the Assessment, Curriculum, and Scheduling teams plan, build, review, test, and release. Hold the line on consistency across all three without flattening what makes each cloud distinct.
• Day-to-day execution: Sprint health, throughput, and delivery against quarterly commitments are yours. Run the cadence through your engineering managers, clear blockers fast, and make the trade-off calls when scope, quality, and timeline collide.
• Quality and reliability: Own the quality bar for core product — driving down Change Failure Rate and Escaped Defect Rate, keeping the bug backlog contained, holding SLA compliance across all severity tiers, and protecting production availability. Quality is a first-class outcome, not a cleanup task.
• People leadership: Lead and grow a team of engineering managers and their pods. Hire, level, coach, and develop EMs; run calibration and performance cycles; build a bench. You are a manager of managers.
• Cross-functional partnership: Operate as the engineering counterpart to product, design, and customer-facing leadership for the three clouds. Translate roadmap into deliverable specs and plans, surface risk early and honestly, and keep commitments realistic and met.
• Engineering operating system: Strengthen the practices that make delivery compound rather than erode — spec quality, estimation discipline, definition of done, code review standards, release process, and metrics that tell the truth about where teams actually stand.

Outcomes you'll be measured on:

• AI and spec-driven adoption — teams operating on a spec-driven model, with measurable velocity and quality gains from AI-assisted development
• Epic completion rate across the three clouds against quarterly goals
• Bug backlog containment — resolved-vs-created trending the right way, total open issues controlled
• Quality signals — Change Failure Rate and Escaped Defect Rate, severity-weighted
• SLA compliance across Urgent / High / Medium / Low tiers
• Delivery predictability — DORA metrics (deployment frequency, lead time, MTTR, change failure rate) and consistent sprint commitment hit-rates
• Production reliability and availability for core product
• Team health — retention, engagement, and EM growth
• Continuous improvement — quarter-over-quarter gains in delivery and quality metrics that show the system is getting better, not just holding

What You'll Bring:

• 10+ years in software engineering with 5+ years leading engineering teams, including managing engineering managers (manager-of-managers experience required)
• Track record running multiple teams or product lines simultaneously and delivering predictably at scale
• Experience leading an AI transformation of an engineering org — driving adoption of AI-assisted development and/or spec-driven practices, and raising the quality bar as AI-generated code volume increases
• A metrics-driven leadership style — fluency with delivery and quality metrics (DORA, defect/escape rates, SLA attainment) and the judgment to know when a metric is a floor vs. a goal
• Demonstrated ability to hold teams accountable — set clear commitments, follow through on outcomes, and address performance directly
• Demonstrated ownership of engineering quality and reliability — not just feature throughput
• A record of building a continuous-improvement culture — where standards rise and the system measurably improves over time
• Strong operating instincts: can walk into a portfolio of in-flight work, quickly read where it actually stands, and make calls
• Excellent cross-functional partnership with product and customer-facing teams; clear, candid communication with executives
• B2B SaaS experience; bonus for complex, integration-heavy, multi-tenant products
• Familiarity with a cloud/pod model and modern delivery tooling (Jira, CI/CD with continuous deployment, observability, automated testing)

Nice to have

• Higher-education technology or other regulated/enterprise vertical experience
• Background scaling teams through rapid growth and process maturation
• Hands-on experience standing up spec-driven workflows or AI development tooling at team or org scale

First 6–12 Months

• First 90 days: Build trust with your EMs and partners, get a true read on delivery and quality health across all three clouds, establish a consistent operating cadence, and set the baseline metrics and the vision for the spec-driven, AI-augmented model.
• By 6 months: Quality and delivery metrics trending in the right direction, commitment hit-rates stabilized, an EM development plan in place, and spec-driven practices piloted and showing early velocity and quality gains.
• By 12 months: Core product engineering is a predictable, high-quality delivery engine — clouds execute consistently on a spec-driven, AI-accelerated model, the backlog is contained, continuous improvement is the norm, and the VP of Engineering can fully trust core product to run.

Not sure if you should apply? Research shows that women and people from underrepresented backgrounds are less likely to apply unless they meet every qualification listed. At Coursedog, we're focused on finding the best person for the role, and that person may come from a non-traditional background. We encourage you to apply even if you don't meet every requirement — our evaluation focuses on your ability to thrive in this role and make an impact.