FREE ACCESS
5,000–10,000 jobs/day
See all jobs on Scoutfield
Search thousands of fresh jobs every day.
Discover
- Fresh listings
- Fast filters
- No subscription required
Create a free account and start exploring right away.
SVP, Head of Development Practices – AI Product Development Lifecycle
LPL Financial. Define and own the target-state AI-native Product Development Lifecycle, including its vision, principles, operating model, stage gates, decision rights, roles, success measures, and multi-year transformation roadmap .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in AI-native Product Development Lifecycle (PDLC) design and implementation, with a strong focus on enterprise-scale delivery transformation, team model design, and governance. Proven ability to lead organizational change, embed compliance and risk controls, and drive strategic alignment across product and engineering teams.
Highest-signal resume keywords
AI-Native Software DevelopmentEnterprise-Scale Delivery TransformationEnd-to-End PDLC DesignExecutive LeadershipCompliance and Risk Management
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Product Development LifecycleDevOpsCI/CDPlatform EngineeringQuality EngineeringWorkflow AutomationAgent FrameworksPrompt EngineeringAutomationHuman Oversight
Soft Skills
Executive CommunicationCross-Functional PartnershipChange LeadershipCoachingPerformance Expectations
Tools & Technologies
IDE IntegrationsTest AutomationObservability ToolsKnowledge SystemsAgent Orchestration Platforms
Industry Keywords
Information SecurityPrivacyComplianceRisk ManagementAudit Controls
Tech Stack
Tools & technologiesSDLC
About the role
Key responsibilities & impact- Define and own the target-state AI-native Product Development Lifecycle, 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 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
- Lead organizational transformation and workforce evolution, including role redesign, skills development, hiring strategy, change leadership, performance expectations, coaching, and adoption support
- Establish governance and executive reporting for PDLC maturity, adoption, exceptions, risks, investment needs, and realized value
- Build, lead, and mentor a high-performing leadership team responsible for PDLC strategy, platform enablement, transformation delivery, engineering excellence, and developer experience
- Report directly to the Chief Technology Officer
Requirements
What you’ll need- 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
Benefits
Comp & perks- 401K matching
- Health benefits
- Employee stock options
- Paid time off
- Volunteer time off
- Competitive LPL Total Rewards package