About our 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.

About 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. This 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 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 quality-related rework
• Establish common quality engineering expectations, patterns, and scorecards where they create meaningful value
• Ensure quality is embedded throughout the software development lifecycle and treated as an engineering capability, not a downstream gate
• Partner closely with engineering leaders across product engineering, platform engineering, infrastructure, security, and planning to improve engineering outcomes
• Collaborate with leaders to ensure delivery, quality, and AI enablement practices support real engineering needs and business priorities
• Coordinate with platform and architecture leaders where standards, tooling, developer workflows, and shared engineering services intersect
• Partner with infrastructure, operations, and security leaders on release readiness, operational effectiveness, engineering controls, and safe adoption of modern development practices
• Align engineering effectiveness practices with planning, sequencing, and cross-functional delivery reviews to improve forecast quality and reduce execution friction
• Support the CTO and senior leadership team with engineering effectiveness insights, recommendations, and progress reporting

REQUIRMENTS

• 10+ years of experience in software engineering, engineering leadership, engineering effectiveness, developer productivity, quality engineering, or related technology leadership roles
• Experience leading engineering teams or engineering leaders and driving improvement through data, metrics, and operating rhythms
• Demonstrated success improving engineering delivery, quality outcomes, and organizational effectiveness across multiple teams or portfolios
• Strong understanding of modern software engineering practices, including software delivery, quality engineering, DevOps, developer workflows, operational excellence, and the implications of AI-assisted and agent-enabled development
• Strong proficiency with AI-assisted and agent-enabled software development, with the ability to evaluate tools, workflows, and engineering implications with credibility
• Demonstrated experience leading engineering teams that have shipped AI-assisted or agent-enabled workflows into production, not just piloted or experimented with them
• Strong understanding of how AI is changing engineering productivity, quality, team practices, and operating models
• Experience leading cross-functional engineering improvement initiatives in a matrixed environment
• Strong ability to influence engineering leaders and drive adoption of better ways of working through credibility, collaboration, data, and practical execution
• Strong people leadership capability, including building and developing high-performing cross-functional teams
• Demonstrated ability to partner effectively across engineering, infrastructure, security, and business stakeholders

Preferred Qualifications

• Experience leading delivery excellence, quality enablement, engineering effectiveness, developer productivity, or related cross-functional engineering functions
• Experience building or reshaping organizations to support engineering effectiveness and modern software delivery practices at scale
• Experience leading AI enablement, engineering productivity, or engineering transformation efforts in software engineering organizations
• Experience defining engineering practices, guardrails, or operating models for AI-assisted and agent-enabled development at scale
• Experience improving engineering workflows in multi-product, platform, or portfolio-based engineering organizations
• Experience partnering with CTOs and senior engineering leaders on strategic priorities and organizational improvement
• Demonstrated technical credibility with software engineering leaders and teams

Work in a Way That Works for You

We promote a healthy work/life balance across the organisation. We offer an appealing working prospect for our people. With numerous wellbeing initiatives, shared parental leave, study assistance and sabbaticals, we will help you meet your immediate responsibilities and your long-term goals.

Working Pattern

Working flexible hours - flexing the times when you work in the day to help you fit everything in and work when you are the most productive.

About the Business

LexisNexis Legal & Professional® provides legal, regulatory, and business information and analytics that help customers increase their productivity, improve decision-making, achieve better outcomes, and advance the rule of law around the world. As a digital pioneer, the company was the first to bring legal and business information online with its Lexis® and Nexis® services.

U.S. National Base Pay Range: $136,100 - $252,800. Geographic differentials may apply in some locations to better reflect local market rates. If performed in New Jersey, the base pay range is $172,172 - $275,028. This job is eligible for an annual incentive bonus.

We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location.

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