Director Engineering Effectiveness Hybrid in Horsham, PA

About the Role

Director, Engineering Effectiveness – Reporting to the CTO, this role leads a cross‑functional organization focused on improving how engineering teams deliver software across the business and on shaping the engineering operating model for an AI‑first future.

U.S. citizen required. Successful background investigation and Public Trust security clearance required. Must be located near Horsham, PA for a hybrid onsite schedule.

• Lead the engineering effectiveness agenda across the organization, aligned with the CTO's strategic priorities.
• Translate engineering leadership priorities into clear operating rhythms, improvement plans, and measurable initiatives.
• Establish engineering scorecards and review cadences that improve visibility into delivery health, quality, execution risk, and engineering effectiveness.
• Define common expectations and fit‑for‑purpose ways of working where greater consistency improves engineering outcomes.
• Use data, team feedback, and operational observation to identify bottlenecks, reduce friction, and improve how engineering teams plan, build, test, and deliver software in both traditional and AI‑assisted development environments.
• Build durable mechanisms for continuous improvement rather than one‑time transformation efforts.
• Recommend and shape the additional capabilities, roles, and support needed to improve effectiveness at scale.
• Define effectiveness practices designed for small, durable delivery teams, including how quality gates, delivery rhythms, and planning practices apply at that scale across a portfolio of products.
• Lead the AI Enablement function focused on transforming how engineering teams work through AI‑assisted and agent‑enabled engineering workflows.
• Define and scale AI‑first engineering practices that reflect how agents and AI tools are changing software development, testing, refactoring, and developer workflows.
• Identify high‑value engineering use cases where AI‑assisted and agent‑enabled approaches can materially improve speed, quality, developer experience, or delivery effectiveness.
• Drive adoption of modern developer tooling, AI‑assisted coding practices, and agent‑enabled workflow patterns that deliver measurable value to engineering teams.
• Establish practical standards, guardrails, review patterns, and quality controls for safe and effective use of AI in software engineering in partnership with security, platform, legal, and other relevant leaders.
• Help the organization move from isolated experimentation with AI tools to durable changes in engineering workflows, team practices, and operating models.
• Own the definition, adoption, and scaling of spec‑driven engineering practices, including the governed toolchain that enforces architecture, security, and quality standards across AI coding tools used by engineering teams.
• Define what good looks like at each stage of AI engineering adoption, establish clear benchmarks for measuring where teams are, and drive measurable team progression against those benchmarks.
• Assess where additional tooling, expertise, or organizational support is needed to accelerate adoption and impact.
• Lead the Delivery Excellence function, including scrum masters, delivery leads, and related delivery support roles.
• Improve planning quality, execution discipline, dependency management, and delivery predictability across teams and portfolios.
• Implement delivery practices that improve outcomes without overburdening teams with unnecessary process.
• Provide engineering leaders with clear visibility into delivery health, sequencing options, and execution risks.
• Support engineering leaders in improving forecasting, coordination, flow, throughput, and delivery reliability while preserving their accountability for delivery outcomes.
• Lead the Quality Enablement function as an engineering capability focused on increasing engineering ownership of quality.
• Improve test strategy, automation practices, release readiness, defect prevention, and root‑cause learning across product and platform teams.
• Partner with engineering leaders to increase release confidence and reduce escaped defects, production issues, and…