Delivery Practice Coach - AI Enablement

The Vanguard Group•Charlotte, PA

1d•Hybrid

About The Position

Delivery Practice Coaches help teams meaningfully integrate AI into how they plan, build, test, document, and review software. They act as experienced AI practitioners themselves, using AI in real workflows to validate guidance and reduce uncertainty for teams. Coach product managers, technical leads, and engineering managers on practical, responsible AI usage across real engineering workflows. Use personal hands-on AI experience to validate recommendations and build credibility. Help teams redesign workflows to take advantage of AI while maintaining quality, security, and engineering standards. Translate emerging AI capabilities into clear team practices, guardrails, and learning paths. Address resistance, misuse concerns, and quality risks through coaching and enablement rather than mandates. Help teams and leaders think ahead about how AI is changing the software development lifecycle and what needs to evolve now. Delivery Practice Coaches strengthen how teams deliver by improving execution, reliability, and discipline without adding unnecessary process. Diagnose delivery risks related to quality, reliability, dependencies, and operational health. Coach teams on modern delivery and engineering practices that improve outcomes. Help teams align delivery behaviors and metrics with product and organizational goals. Validate improvements using data, observation, and lightweight experimentation. Partner with engineering and product leaders to resolve recurring delivery challenges. Delivery Practice Coaches help teams improve speed and predictability by removing friction and constraints rather than increasing pressure. Identify bottlenecks, handoffs, and wait states that slow delivery. Use flow metrics and qualitative signals to guide improvement conversations. Design and test targeted, time-boxed experiments to improve throughput and stability to support our efforts at obtaining predictability. Help teams reduce work in progress and simplify workflows. Support leaders in deciding on tradeoffs around scope, sequencing, and capacity. S3 Delivery Practice Coaches primarily operate at the product family level. They influence product managers, technical leads, and engineering managers through hands-on coaching, experimentation, and enablement. While they surface systemic insights and reusable patterns, they are not expected to lead large-scale organizational transformation programs. This role is expected to support a changing and quickly evolving workforce thus the role could take on special projects as assigned.

Requirements

Undergraduate degree or equivalent combination of training and experience required.
Computer Science or Engineering experience preferred.
Minimum of five years related work experience.
8+ years of related work experience is preferred.
Two years of leading large cross-functional teams on major organizational technology projects preferred.
Financial Services and technical experience preferred.

Nice To Haves

Graduate degree preferred.

Responsibilities

Help teams meaningfully integrate AI into how they plan, build, test, document, and review software.
Act as experienced AI practitioners themselves, using AI in real workflows to validate guidance and reduce uncertainty for teams.
Coach product managers, technical leads, and engineering managers on practical, responsible AI usage across real engineering workflows.
Use personal hands-on AI experience to validate recommendations and build credibility.
Help teams redesign workflows to take advantage of AI while maintaining quality, security, and engineering standards.
Translate emerging AI capabilities into clear team practices, guardrails, and learning paths.
Address resistance, misuse concerns, and quality risks through coaching and enablement rather than mandates.
Help teams and leaders think ahead about how AI is changing the software development lifecycle and what needs to evolve now.
Strengthen how teams deliver by improving execution, reliability, and discipline without adding unnecessary process.
Diagnose delivery risks related to quality, reliability, dependencies, and operational health.
Coach teams on modern delivery and engineering practices that improve outcomes.
Help teams align delivery behaviors and metrics with product and organizational goals.
Validate improvements using data, observation, and lightweight experimentation.
Partner with engineering and product leaders to resolve recurring delivery challenges.
Help teams improve speed and predictability by removing friction and constraints rather than increasing pressure.
Identify bottlenecks, handoffs, and wait states that slow delivery.
Use flow metrics and qualitative signals to guide improvement conversations.
Design and test targeted, time-boxed experiments to improve throughput and stability to support our efforts at obtaining predictability.
Help teams reduce work in progress and simplify workflows.
Support leaders in deciding on tradeoffs around scope, sequencing, and capacity.
Operate at the product family level.
Influence product managers, technical leads, and engineering managers through hands-on coaching, experimentation, and enablement.
Surface systemic insights and reusable patterns.
Support a changing and quickly evolving workforce thus the role could take on special projects as assigned.