SVP, Head of Development Practices & AI Product Development Lifecycle

LPL Financial•Fort Mill, SC

3d•$240,000 - $290,000

About The Position

LPL Financial is seeking a senior executive to redefine how enterprise software and digital products are created in an AI-accelerated world. Reporting directly to the Chief Technology Officer, this leader will define, lead, and continuously evolve LPL's target-state Product Development Lifecycle (PDLC). The role will design the operating model, platforms, guardrails, and team structures that enable smaller, higher-leverage teams to deliver faster while strengthening quality, resilience, security, and accountability. The leader will embed agentic workflows, autonomous and semi-autonomous agents, and human-in-the-loop governance across discovery, design, development, testing, deployment, operations, and continuous improvement. Working across Engineering, Product, Architecture, Data & AI, Security, Risk, Legal, Compliance, and business leadership, this role will integrate people, process, platforms, and AI into an observable, auditable, and continuously improving delivery system.

Requirements

Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field.
15 or more years of progressive leadership experience spanning software engineering, product development, platform engineering, or enterprise technology transformation in large, complex organizations.
Proven success leading enterprise-scale delivery transformation, including modern PDLC/SDLC design, DevOps, CI/CD, platform engineering, shift-left quality, operating-model redesign, or product-led delivery.
Demonstrated production experience with AI-assisted and agentic development, including large language model coding assistants, agent frameworks, workflow automation, retrieval-augmented generation or knowledge systems, and human oversight.
Experience embedding security, privacy, compliance, risk, and audit controls into technology delivery within a regulated or similarly control-intensive environment.
Executive leadership, enterprise influence, strategic planning, and technology investment prioritization.
End-to-end PDLC design, DevOps, platform engineering, developer experience, quality engineering, and continuous delivery.
AI-native software development, agent orchestration, prompt and context engineering, automation, and responsible AI governance.
Team topology, operating-model design, workforce transformation, and change leadership.
Executive communication, cross-functional partnership, engineering metrics, and outcome-based accountability.

Nice To Haves

Master's degree in Computer Science, Engineering, Information Systems, Business Administration, or a related discipline.
Experience in financial services, healthcare, or another highly regulated industry, with direct exposure to secure software development, model risk, privacy, audit, and operational resilience requirements.
Cloud, architecture, agile, or DevOps credentials such as AWS, Microsoft Azure, or Google Cloud Solutions Architect; Certified Scrum Professional; SAFe Practice Consultant; or DevOps Institute certification.

Responsibilities

Define and own the target-state AI-native PDLC, including its vision, principles, operating model, stage gates, decision rights, roles, success measures, and multi-year transformation roadmap.
Design the target-state team model for AI-augmented product development, including team composition, agent roles, human-agent collaboration patterns, escalation paths, pilot sequencing, scaling criteria, and migration from current delivery structures.
Establish enterprise standards for agentic development, including agent taxonomy, workflow orchestration, prompt and context management, tool integration, secure data handling, auditability, and human oversight requirements.
Build the PDLC platform and toolchain strategy with Architecture, Platform Engineering, and AI/ML teams across IDE integrations, CI/CD, test automation, observability, knowledge systems, and agent orchestration platforms.
Define and govern outcome-based measures for cycle time, release frequency, quality, defect rates, agent utilization and effectiveness, developer experience, cost-to-deliver, technical debt, operational resilience, and business value.
Partner with Product, Engineering, and business leaders to align PDLC adoption with product strategy, portfolio priorities, modernization objectives, and delivery commitments.
Embed controls with Enterprise Risk, Information Security, Compliance, Legal, Privacy, and Model Risk Management, ensuring responsible AI use and regulatory readiness throughout the development value stream.
Lead organizational transformation and workforce evolution, including role redesign, skills development, hiring strategy, change leadership, performance expectations, coaching, and adoption support for AI-augmented teams.
Establish governance and executive reporting for PDLC maturity, adoption, exceptions, risks, investment needs, and realized value; advise senior leadership on technology strategy, organizational design, and competitive implications.
Build, lead, and mentor a high-performing leadership team responsible for PDLC strategy, platform enablement, transformation delivery, engineering excellence, and developer experience.