Director Engineering Effectiveness* Hybrid in Horsham, PA

Lexis Nexis Reed Tech is a global technology company that provides solutions for the life sciences industry. The Reed Tech suite of Single Source™ and Navigator™ products helps companies manage product data and meet compliance deadlines.

The Director, Engineering Effectiveness reports to the CTO and leads a cross‑functional organization focused on improving how engineering teams deliver software across the business and shaping the engineering operating model for an AI‑first future. The role owns Delivery Excellence, Quality Enablement, and AI Enablement, driving effective, predictable delivery and high‑quality software at scale.

• Lead the engineering effectiveness agenda across the organization, aligned to 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 to increase consistency and engineering outcomes
• Use data, team feedback and operational observation to identify bottlenecks, reduce friction and improve planning, building, testing and delivery in both traditional and AI‑assisted environments
• Build durable mechanisms for continuous improvement rather than one‑time transformation efforts
• Recommend and shape additional capabilities, roles and support needed to improve effectiveness at scale
• Define effectiveness practices for small, durable delivery teams, including quality gates, delivery rhythms and planning practices across a portfolio of products
• Lead the AI Enablement function focused on transforming how engineering teams work through AI‑assisted and agent‑enabled workflows
• Define and scale AI‑first engineering practices that reflect how agents and AI tools are changing development, testing, refactoring and developer workflows
• Identify high‑value AI use cases to improve speed, quality, developer experience and delivery effectiveness
• Drive adoption of modern developer tooling, AI‑assisted coding practices and agent‑enabled workflow patterns that deliver measurable value
• Establish practical standards, guardrails, review patterns and quality controls for safe AI usage in partnership with security, platform, legal and other leaders
• 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
• Define benchmarks and drive measurable progression against AI engineering adoption stages
• Assess tooling, expertise and organizational support needed to accelerate AI adoption and impact
• Lead the Delivery Excellence function, including scrum masters, delivery leads and related support roles
• Improve planning quality, execution discipline, dependency management and delivery predictability across teams and portfolios
• Implement delivery practices that improve outcomes without unnecessary process burden on teams
• Provide engineering leaders with visibility into delivery health, sequencing options and execution risks
• Support leaders in forecasting, coordination, flow, throughput and delivery reliability while preserving accountability for outcomes
• Lead the Quality Enablement function focused on engineering ownership of quality
• Improve test strategy, automation practices, release readiness, defect prevention and root‑cause learning across product and platform teams
• Partner with leaders to increase release confidence and reduce escaped defects, production issues and quality‑related rework
• Establish common quality engineering expectations, patterns and scorecards that create real value
• Embed quality throughout the software development lifecycle as an engineering capability, not a downstream gate
• Collaborate with platform and architecture leaders where standards, tooling, developer workflows and shared services intersect
• Partner across infrastructure, operations, security and business stakeholders for release readiness, operational effectiveness and safe AI adoption
• Align…