Manager Lead Devsecops Engineer Jobs in Oklahoma

Overview

As a Delivery Leader, you are a senior member of the Delivery capability accountable for portfolio-level coordination across products, functions, stakeholders, and large initiatives orchestrating execution across many moving parts does not coordinate itself. Delivery Leaders own orchestration of stakeholder alignment at enterprise scale, dependency management on programs spanning multiple products and functions, and judgment about how to sequence work when constraints conflict.

With a strong focus on operational excellence, customer-centric problem-solving, innovation, and continuous improvement, you will guide teams to achieve peak performance and deliver high-quality outcomes on time and within budget. The ideal candidate is a visionary leader and mentor committed to driving success for Deloitte's clients and business investments.

Recruiting for this role ends on 31 August, 2026.

What You Will Own

• Portfolio-level delivery coordination: Orchestrate execution across multiple product teams, service lines, and enterprise functions. Hold the cross-team view that no single product team can hold for itself.
• Stakeholder orchestration: Hold the relationship with internal Deloitte stakeholders at the program level, service line leaders, function heads, platform owners and reconcile the cross-stakeholder inconsistencies that show up at scale.
• Delivery operating model: Own how Delivery work is governed in your portfolio. Define the templates, intake patterns, evidence gates, and exception paths that allow AI-assisted execution to scale without losing accountability.
• AI-augmented delivery practice: Direct AI agents and assistants in delivery workflows - what they coordinate, what evaluation criteria apply, and where exceptions route to humans.
• Own end-to-end LLM, agentic AI, and cloud consumption costs-governing model selection, orchestration, token usage, and infrastructure efficiency through FinOps practices.
• Drive Applied AI delivery budget planning, forecasting, and tracking aligned to ROI targets, enforcing financial governance and surfacing cost-saving opportunities within defined guardrails.
• Capability stewardship: Coach Delivery Managers in your portfolio. Develop the senior coordination talent the organization needs.

Core Responsibilities

1. Strategic Vision and Alignment: Lead large-scale, AI-native implementations and ensure each program delivers the outcome its charter promised, right-sizing program structures to scale and partnering with Product, Engineering, Architecture, and Experience leaders to hold the strategic line.
2. Evangelism: Inspire teams and educate the organization on product engineering models, actively experimenting with GenAI so the discovery and delivery practices you advocate stay current.
3. Craft Mastery and Objectives Realization: Drive evidence-gated delivery - work advances when deployed evidence confirms intended behavior, not at a sprint boundary - and define the standards, evaluation criteria, and exception handling by which AI agents participate in delivery, using telemetry and audit trails for quality and KPI tracking.
4. Capability Evolution and Development: Coach and calibrate Delivery Managers, building their fluency in AI-native discovery and delivery methodologies and growing the Delivery community of practice.
5. Operational Excellence: Run alignment cadence at the level the work demands, and embed continuous, evidence-backed governance in the pipeline (policy as code, telemetry, immutable audit trails) rather than periodic gates - carrying programs through operate with durable accountability.
6. Customer-Centric Problem Solving: Anchor teams to the charter outcome, treating "deployed evidence confirms intended behavior" as the real definition of done, and carry initiatives into adoption so value lands in the customer's hands.
7. Expert Proficiency and Continuous Improvement: Keep the engineering model lean by governing intake of AI-generated artifacts so they become productive inputs rather than noise, defining how AI agents operate in workflows, and using evidence gates to cut work that isn't earning its place.
8. Communication: Reconcile conflicting stakeholder and AI-drafted artifacts on the same initiative, run the forums where alignment happens, and escalate deliberately - surfacing trade-offs and holding the room until a decision is made.
9. Delivery Risk Management: Manage dependencies across products and platforms, using evidence-gated cycles, continuous governance, and audit trails as the primary risk controls to surface issues early and decide contingencies before they become incidents.
10. Organizational Engagement and Collaboration: Engage stakeholders across Product, Experience, and Engineering, govern AI-generated artifact intake as a partnership, and model senior Delivery behaviors: judgment under uncertainty, stakeholder steadiness, and evidence orientation.

The Team

US Deloitte Technology Product Engineering has modernized software and product delivery, creating a scalable, cost-effective model that focuses on value and outcomes. As Deloitte's primary product development team, Product Engineering delivers innovative digital solutions to businesses, service lines, and internal operations with proven bottom-line results. We develop and deploy cutting-edge go-to-market solutions that help Deloitte operate effectively and lead the market. Our reputation is built on a tradition of delivering excellence.

Qualifications

Required Experience

• Experience: 15+ years of progressive delivery leadership experience in product engineering, enterprise technology, or management consulting environments.
• Demonstrated track record leading large, cross-functional programs - defined as programs with multiple product teams, multiple stakeholders, and meaningful cross-function dependencies.
• Direct experience with both Agile/Lean operating models and the emerging intent-driven, evidence-gated delivery patterns.
• Experience working in a product-staffed model where durable product teams stay with their products across build, deploy, operate, and evolve.
• Strong expertise in AI/Cloud FinOps, budget management, financial forecasting, vendor management, cost optimization, and data-driven delivery governance.
• Prior experience coaching Delivery Managers or Program Managers.
• Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve.
• Limited immigration sponsorship may be available.

Required Skills

• Engineering fluency: Comfortable in technical conversations with architects and senior engineers; able to challenge feasibility claims and reason about trade-offs without needing translation.
• Stakeholder orchestration at scale: Track record of holding alignment across senior internal stakeholders with competing priorities.
• Evidence orientation: Comfortable measuring delivery by outcome validation rather than velocity proxies.
• AI-augmented working practice: Fluent with current GenAI assistants and agentic delivery tooling. Able to direct AI output and design where AI agents fit in delivery workflows and where humans must remain in the loop.
• Communication: Exhibit excellent communication skills to inspire and influence stakeholders. Serve as the contact for value achievement and collaborate with product engineering teams. Facilitate co-creation workshops to foster alignment and decision-making

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $124,600 to $255,900.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

Qualifications:

Overview

As a Delivery Leader, you are a senior member of the Delivery capability accountable for portfolio-level coordination across products, functions, stakeholders, and large initiatives orchestrating execution across many moving parts does not coordinate itself. Delivery Leaders own orchestration of stakeholder alignment at enterprise scale, dependency management on programs spanning multiple products and functions, and judgment about how to sequence work when constraints conflict.

With a strong focus on operational excellence, customer-centric problem-solving, innovation, and continuous improvement, you will guide teams to achieve peak performance and deliver high-quality outcomes on time and within budget. The ideal candidate is a visionary leader and mentor committed to driving success for Deloitte's clients and business investments.

Recruiting for this role ends on 31 August, 2026.

What You Will Own

• Portfolio-level delivery coordination: Orchestrate execution across multiple product teams, service lines, and enterprise functions. Hold the cross-team view that no single product team can hold for itself.
• Stakeholder orchestration: Hold the relationship with internal Deloitte stakeholders at the program level, service line leaders, function heads, platform owners and reconcile the cross-stakeholder inconsistencies that show up at scale.
• Delivery operating model: Own how Delivery work is governed in your portfolio. Define the templates, intake patterns, evidence gates, and exception paths that allow AI-assisted execution to scale without losing accountability.
• AI-augmented delivery practice: Direct AI agents and assistants in delivery workflows - what they coordinate, what evaluation criteria apply, and where exceptions route to humans.
• Own end-to-end LLM, agentic AI, and cloud consumption costs-governing model selection, orchestration, token usage, and infrastructure efficiency through FinOps practices.
• Drive Applied AI delivery budget planning, forecasting, and tracking aligned to ROI targets, enforcing financial governance and surfacing cost-saving opportunities within defined guardrails.
• Capability stewardship: Coach Delivery Managers in your portfolio. Develop the senior coordination talent the organization needs.

Core Responsibilities

1. Strategic Vision and Alignment: Lead large-scale, AI-native implementations and ensure each program delivers the outcome its charter promised, right-sizing program structures to scale and partnering with Product, Engineering, Architecture, and Experience leaders to hold the strategic line.
2. Evangelism: Inspire teams and educate the organization on product engineering models, actively experimenting with GenAI so the discovery and delivery practices you advocate stay current.
3. Craft Mastery and Objectives Realization: Drive evidence-gated delivery - work advances when deployed evidence confirms intended behavior, not at a sprint boundary - and define the standards, evaluation criteria, and exception handling by which AI agents participate in delivery, using telemetry and audit trails for quality and KPI tracking.
4. Capability Evolution and Development: Coach and calibrate Delivery Managers, building their fluency in AI-native discovery and delivery methodologies and growing the Delivery community of practice.
5. Operational Excellence: Run alignment cadence at the level the work demands, and embed continuous, evidence-backed governance in the pipeline (policy as code, telemetry, immutable audit trails) rather than periodic gates - carrying programs through operate with durable accountability.
6. Customer-Centric Problem Solving: Anchor teams to the charter outcome, treating "deployed evidence confirms intended behavior" as the real definition of done, and carry initiatives into adoption so value lands in the customer's hands.
7. Expert Proficiency and Continuous Improvement: Keep the engineering model lean by governing intake of AI-generated artifacts so they become productive inputs rather than noise, defining how AI agents operate in workflows, and using evidence gates to cut work that isn't earning its place.
8. Communication: Reconcile conflicting stakeholder and AI-drafted artifacts on the same initiative, run the forums where alignment happens, and escalate deliberately - surfacing trade-offs and holding the room until a decision is made.
9. Delivery Risk Management: Manage dependencies across products and platforms, using evidence-gated cycles, continuous governance, and audit trails as the primary risk controls to surface issues early and decide contingencies before they become incidents.
10. Organizational Engagement and Collaboration: Engage stakeholders across Product, Experience, and Engineering, govern AI-generated artifact intake as a partnership, and model senior Delivery behaviors: judgment under uncertainty, stakeholder steadiness, and evidence orientation.

The Team

US Deloitte Technology Product Engineering has modernized software and product delivery, creating a scalable, cost-effective model that focuses on value and outcomes. As Deloitte's primary product development team, Product Engineering delivers innovative digital solutions to businesses, service lines, and internal operations with proven bottom-line results. We develop and deploy cutting-edge go-to-market solutions that help Deloitte operate effectively and lead the market. Our reputation is built on a tradition of delivering excellence.

Qualifications

Required Experience

• Experience: 15+ years of progressive delivery leadership ...