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Director Engineering Effectiveness Hybrid in Horsham, PA

Job in Horsham, Montgomery County, Pennsylvania, 19044, USA
Listing for: LexisNexis
Full Time position
Listed on 2026-07-19
Job specializations:
  • Software Development
    Software Project Mgr/ Lead, AI Engineer (Applied/Software), Software Architect
Salary/Wage Range or Industry Benchmark: 136100 - 252800 USD Yearly USD 136100.00 252800.00 YEAR
Job Description & How to Apply Below
Position: Director Engineering Effectiveness*** Hybrid in Horsham, PA

Overview

Lexis Nexis Reed Tech brings clarity to innovation for businesses worldwide. We enable innovators to accomplish more by helping them make informed decisions, be more productive, comply with regulations, and ultimately achieve a competitive advantage for their business. Our Reed Tech suite of Single Source® for Medical Devices, Single Source® for Drug Products, and Navigator® for Drug Labels enables life sciences companies to create product data management strategies and meet compliance deadlines on time.

For more information, visit

The Team

Reporting to the CTO, the Director, Engineering Effectiveness will lead 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. This leader will own Delivery Excellence, Quality Enablement, and AI Enablement, with accountability for improving engineering effectiveness, delivery predictability, release confidence, and driving the organization’s progression from teams using AI tools alongside traditional practices, through AI‑led workflows with human oversight, toward increasingly autonomous delivery at scale.

The Role

The Director will lead existing capabilities while helping define how engineering teams work in an environment where agents play an increasing role in code generation, testing, refactoring, and workflow execution. This leader will help the organization move beyond optimizing legacy engineering practices and instead build the mechanisms, guardrails, capabilities, and ways of working needed for durable AI‑first software development. The role partners closely with engineering leaders across product engineering, platform engineering, infrastructure, security, and planning.

It does not replace engineering leader accountability for delivery within their organizations; instead, it owns the cross‑cutting capabilities, practices, and enablement needed to help teams deliver more effectively and consistently across the organization.

Conditions of Employment

You must be a U.S. citizen to apply for this position.

You must successfully pass a background investigation and achieve Public Trust security clearance.

Must be located near the Horsham, PA location for a Hybrid onsite schedule.

Accountabilities
  • 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 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…
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