The Technical Program Engagement & Automation Manager is a hands‑on technical leader responsible for driving Agile Release Train (ART) execution, building enterprise-grade automation, and advancing the use of Agentic AI to accelerate delivery. This role is ideal for an experienced software developer turned program manager—someone who combines deep engineering expertise with strategic program leadership.

You will partner with engineering, product, and enterprise technology teams to design automated workflows, reduce delivery friction, enhance operational efficiency, and enable scalable AI-supported processes across the organization.

Key Responsibilities

Agile Release Train (ART) Leadership & SAFe Delivery

• Lead the planning, execution, and operational cadence of the ART, ensuring predictable and high‑quality value delivery.
• Apply SAFe principles to optimize flow, manage dependencies, and improve team alignment and performance.
• Collaborate with System Architects, Product Management, and Change & Release Automation to ensure technical integrity and solution consistency.
• Track ART metrics, identify performance bottlenecks, and lead continuous improvement activities.

Technical Development & Automation Engineering

• Leverage strong software development experience to design, code, and deploy automated solutions that eliminate manual effort across program, development, testing, deployment, and business processes.
• Build reusable automation assets using scripting, API integration, low-code tools, and CI/CD pipeline enhancements.
• Partner with engineering teams to integrate intelligent automation into DevOps workflows and platform operations.
• Establish standards, guardrails, and best practices for scalable automation.

Agentic AI Strategy & Implementation

• Design and implement agent-based AI workflows to augment team productivity, accelerate decision-making, and automate complex processes.
• Develop LLM-driven copilots, orchestrated agents, and self-guided automation routines using enterprise AI platforms.
• Serve as a technical advisor for Process & Programs on AI adoption, safety, governance, and prompt engineering.
• Identify and validate high-value AI use cases aligned with operational and programmatic goals.

Program Engagement & Cross-Functional Leadership

• Act as the primary interface for technical engagement across product, engineering, architecture, and business stakeholders.
• Communicate program priorities, risks, dependencies, and progress through clear, data-driven insights.
• Foster strong relationships across teams to ensure adoption of automation and AI capabilities.
• Facilitate organizational change management and training to drive adoption of new technologies and workflows.

Operational Excellence & Governance

• Maintain transparency across the ART through dashboards, documentation, artifacts, and reporting structures.
• Manage compliance, risk, and quality controls for automation and AI-enabled processes.
• Ensure alignment with enterprise engineering standards, security policies, data governance, and architecture frameworks.

Required Qualifications

• 7+ years of experience in software development or engineering roles, with hands-on coding experience.
• 3+ years of technical program management or Agile leadership.
• Proven experience leading SAFe-based development and ART execution.
• Strong experience building automated workflows, integrations, or pipeline automation.
• Demonstrated ability to implement AI-driven or Agentic AI automation in operational or technical contexts.
• Excellent communication, facilitation, and stakeholder management skills.
• Strong problem-solving capabilities with a continuous improvement mindset.

Preferred Qualifications

• SAFe certifications (e.g., SA, SASM, RTE, SPC).
• Experience with LLM orchestration, autonomous agents, and AI workflow automation platforms.
• Background in cloud-native development (Azure, AWS, GCP).
• DevSecOps experience (pipelines, IaC, testing automation).
• Experience leading teams through modernization or AI/automation transformation initiatives.

Success Measures

• Increased ART predictability, velocity, and delivery throughput.
• Significant reduction in manual processes through automation and AI.
• Improved operational visibility and decision-making for stakeholders.
• High adoption and satisfaction with automated and AI-enabled workflows.
• Measurable improvements in team productivity and time-to-value.