Associate Director, Product Software Engineering

Wolters Kluwer•Coppell, TX

1d•$144,500 - $258,300

About The Position

The Associate Director, Product Software Engineering leads multiple engineering teams responsible for building, modernizing, and operating business-critical customer and internal applications across FCC CLC. The role translates product and business priorities into executable engineering strategies, establishes accountability for delivery and quality, and develops teams that deliver measurable customer outcomes. The position combines strategic leadership with technical judgment. It partners with Product Management, Architecture, Quality Engineering, UX, Operations, Security, and other technology leaders to guide initiatives from initial intent through specification, architecture, implementation, validation, deployment, and production operation. It enforces Spec-Driven Development (SDD) and Agentic Product Development Lifecycle (PDLC) practices and builds AI engineering capability by hiring, managing, coaching, and mentoring AI engineers responsible for agentic product workflows.

Requirements

Bachelor’s degree in Computer Science, Software Engineering, Information Systems, or a related field, or equivalent practical experience.
10+ years of significant experience leading software engineering organizations responsible for enterprise or commercial software products.
1+ years of hands-on experience applying Agentic Product Development Lifecycle and Spec-Driven Development to product delivery.
1+ years of hands-on experience leading agentic product workflow development, including evaluation frameworks, context engineering, learning and feedback loops, end-to-end traceability, and architecture approaches that optimize token consumption and operating cost.
Demonstrated experience hiring, managing, coaching, and mentoring AI engineers and building high-performing teams capable of delivering reliable AI-enabled product capabilities.
Demonstrated experience managing managers or multiple engineering teams in a matrixed, globally distributed environment.
Experience delivering and operating native, highly available, secure, and business-critical cloud software.
Experience guiding legacy application modernization while sustaining production operations and customer commitments.
Experience using metrics and evidence to improve delivery predictability, quality, reliability, and engineering effectiveness.
Strong people leadership, organizational design, coaching, conflict resolution, and talent-development capabilities.
Strong technical judgment and the ability to challenge assumptions and facilitate sound architecture and engineering decisions.
Ability to connect customer and business outcomes to technology strategy, delivery priorities, and investment choices.
Executive-level communication and ability to influence across Product, Engineering, Operations, Security, and business leadership.
Ability to lead through ambiguity, establish structure, and make timely decisions using incomplete information.
Commitment to inclusive leadership, use of AI, continuous learning, and responsible delivery.

Nice To Haves

Master’s degree in a relevant technical or business discipline.

Responsibilities

Lead multiple software engineering teams and establish goals, operating rhythms, ownership boundaries, and measurable outcomes.
Translate portfolio strategy and product priorities into engineering roadmaps, staffing plans, delivery commitments, and technical investment decisions.
Make decisions about prioritization, resource allocation, technical direction, delivery risk, and sequencing across concurrent initiatives.
Build an engineering culture grounded in customer focus, accountability, psychological safety, technical excellence, and continuous improvement.
Coach engineering managers, technical leads, AI engineers, and senior software engineers; strengthen succession plans and support career growth.
Hire, manage, coach, and mentor AI engineers, building the skills and delivery practices needed to develop reliable agentic product capabilities.
Enforce SDD and Agentic PDLC practices, including reusable specifications, explicit acceptance criteria, evaluation strategies, and end-to-end traceability.
Ensure architecture, security, privacy, accessibility, resilience, scalability, observability, and supportability are considered throughout the lifecycle.
Ensure effective DevOps practices across CI/CD, IaC, hands-free deployments, telemetry, monitoring, and alerting, using DORA and operational metrics to improve delivery and production excellence.
Establish quality as a shared accountability across engineering and quality functions, with appropriate automation, release criteria, and production validation.
Improve engineering flow by identifying and removing systemic blockers, reducing avoidable handoffs, and strengthening cross-team dependency management.
Use delivery, quality, reliability, customer, and engineering-effectiveness measures to identify trends and drive corrective action.
Support production operations, incident response, root-cause analysis, and remediation of recurring reliability or quality issues.