Manager, Intelligent Automation and AI Delivery

How will this role impact First Command?

First Command is seeking a delivery‑focused leader to manage the Intelligent Automation capability, unifying Robotic Process Automation (RPA) and AI engineering into a single high‑performing team.

This leader will:

• Oversee execution of rule‑based, probabilistic, and hybrid automation solutions.
• Ensure alignment with enterprise priorities and maintain strong delivery discipline.
• Reinforce responsible innovation and embed risk‑aware practices across the automation lifecycle.

The role is accountable for managing a multidisciplinary engineering team, maintaining product and backlog hygiene, partnering with business stakeholders to identify and prioritize high‑impact opportunities, and supporting ongoing team development across both RPA and AI functions.

What will the employee do in this role?

Leadership & People Management

• Lead, mentor, and develop a cross-functional team of RPA developers and AI engineers.
• Foster a culture of innovation, responsible AI practices, collaboration, and continuous improvement.
• Provide coaching, performance management, career development, and resource allocation.
• Promote alignment on engineering best practices across RPA and AI development disciplines.
• Embed responsible automation principles into team development and onboarding

Product Management & Ownership

• Serve as Product Owner for the Intelligent Automation capability.
• Maintain the automation roadmap across rule‑based, probabilistic, and hybrid solutions.
• Ensure backlog hygiene with clear feature definitions, refined user stories, and acceptance criteria.
• Prioritize work based on business value, risk, impact, and strategic objectives.
• Partner with Architecture and Quality teams to uphold engineering standards and lifecycle processes.
• Ensure all automation solutions comply with privacy, security, and regulatory requirements.
• Maintain documentation and audit trails supporting compliance and incident.

Stakeholder Engagement

• Collaborate with business leaders to identify automation opportunities across RPA, advanced analytics, and AI-driven workflows.
• Facilitate discovery workshops and intake sessions to understand business requirements and pain points.
• Translate business needs into actionable technical requirements for both RPA and AI engineering teams.
• Communicate roadmap progress, risks, KPIs, and delivery timelines to stakeholders and senior leadership.

Technical Oversight & Delivery Management

• Oversee development, deployment, monitoring, and continuous improvement of automation solutions.
• Ensure adherence to best practices across RPA, AI model development, security, and responsible AI guidelines.
• Monitor production performance, KPIs, and scalability of deployed automation.
• Guide integration of AI solutions and RPA workflows into cohesive intelligent automation products.
• Drive reusability, standardization, and documentation across automation assets.
• Implement ongoing assessments and reviews to mitigate technical, ethical, and operational risks.
• Support continuous feedback loops and report compliance‑related metrics to executive leadership

Who will this employee lead? 

• Lead a team of between 3 and 8 engineers providing day-to-day supervision and as well as ongoing performance and career management.
• Support recruiting, interviewing, and onboarding of new team members.
• Promote professional development and continued upskilling in both RPA and modern AI engineering practices, embedding governance literacy and compliance awareness into training.
• Track team performance metrics, including adherence to governance, risk, and compliance standards, and report outcomes to Senior Leadership.
• Ensure onboarding and performance management processes incorporate documentation, risk awareness, and compliance with internal and external policies throughout the employee lifecycle

What skills & qualifications will this employee need?

Education

• Preferred: Bachelor's Degree in Information Systems, Computer Science, Engineering, Business, or related field.
• Preferred: Product Owner, Product Manager, or Scrum Master certifications.
• Preferred: Certifications in RPA tools (UiPath, Power Platform) and/or AI/ML engineering
• Nice to have: Training or certification in AI governance, risk management, or compliance frameworks (e.g., ISO/IEC 42001, NIST AI RMF, Responsible AI or similar).

Work Experience

• 3+ years of people management experience in technical, automation, or AI-focused teams.
• 6–8 years of experience in Information Technology, automation engineering, AI/ML engineering, or related fields.
• Nice to have: Experience implementing governance, risk, and compliance (GRC) processes for AI and automation initiatives.

Required Knowledge, Skills, and Abilities

Required:

• Hands-on experience building automation development (UiPath, Microsoft Power Platform, Azure Foundry).
• Understanding of modern AI/ML concepts including LLM-based agents, orchestration frameworks, and prompt engineering.
• Experience with backlog management, product lifecycle, and Agile/Scrum methodologies.
• Strong communication skills, capable of effectively navigating between business and technical audiences.
• Strong troubleshooting, debugging, and analytical skills.
• Knowledge of metrics development, reporting, and value realization frameworks.
• Demonstrated ability to apply governance, risk management, and compliance principles to automation and AI projects.
• Ability to maintain documentation and audit trails for AI and automation assets, supporting compliance and incident response.
• Familiarity with responsible AI principles-Validity and Reliability, Accountability, Fairness and Bias, Safety and Security, Data Privacy, Explainability and Transparency.

Preferred:

• Experience in Financial Services domain.
• Familiarity with model governance, responsible AI practices, and MLOps MLOps.

Nice to Have:

• Experience conducting risk assessments, threat modeling, and fairness audits for AI systems.
• Knowledge of evolving regulatory requirements for AI (e.g., NIST AI RMF).

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