Director, Data and AI Enablement (Remote)

Date Posted:

2026-06-24

Country:

United States of America

Location:

US-CT-REMOTE

Position Role Type:

Remote

U.S. Citizen, U.S. Person, or Immigration Status Requirements:

Must be authorized to work in the U.S. without the company’s immigration sponsorship now or in the future. The company will not offer immigration sponsorship for this position.​ The company will not seek an export authorization for this role.

Security Clearance Type:

None/Not Required

Security Clearance Status:

Not Required

At RTX, the world largest aerospace and defense company, 185,000 great minds are united by purpose and inspired to make a difference solving the world’s most complex problems.

With our three market leading businesses, world-class operations and investments in research and development, we offer capabilities and opportunity no one else can. Together, we push the boundaries of known science and find new ways to connect and protect our world. 

Pratt & Whitney is a world leader in the design, manufacture and service of aircraft engines and auxiliary power systems and has been revolutionizing modern flight for over 100 years.

Join us and help shape the future of aerospace and defense.

The Pratt & Whitney Digital and Analytics team has an immediate remote opportunity for a Director of Data and AI Enablement.

What You Will Do:

Our Digital and Analytics teams play a critical role in that mission by advancing the data, technologies, and digital capabilities that improve how we design, manufacture, and support the next generation of aerospace solutions.

The Director of Data and AI Enablement is a global Digital Technology leader responsible for the data engineering, AI engineering, and foundational services that enable high-quality, accessible, and reliable data across the enterprise.

This role focuses on making data from diverse sources—including IoT, field operations, and factory and production systems—ready, trusted, and usable for analytics, AI, and operational decision-making.

This leader ensures data and AI engineering capabilities are modern, secure, reliable, and fully compliant with global trade, regulatory, export control, and data residency requirements, while avoiding duplication and enabling scalable enterprise use.

The role partners across the full Digital Technology and business landscape to deliver unified and scalable data and AI capabilities for the company.

Key Responsibilities:

Enterprise Data & AI Engineering Strategy:

- Set and lead the strategy for data engineering, AI engineering, and foundational data services, ensuring scalability, efficiency, and alignment to business outcomes.

End-to‑End Data and AI Enablement Lifecycle:

- Ensure an end‑to‑end lifecycle from diverse raw data sources—including IoT, field data, and factory/production systems—through engineering, modeling, deployment, monitoring, and operational insight.

Data Architecture, Engineering, and Operational Integration:

- Lead global teams across data architecture, data engineering, integration engineering, and data operations.

- Establish and enforce standards for coding, observability, resiliency, SLIs and SLOs, incident response, and operational playbooks.

- Align architecture and engineering practices with governance frameworks, domain models, security standards, and capability stability requirements.

AI Capability Engineering, MLOps, and AI Ops:

- Own global AI capability capabilities including compute environments, MLOps tooling, AI operational workflows, and model hosting capabilities.

- Ensure AI environments meet standards for security, performance, availability, compliance, and cost optimization.

- Deliver reusable AI capability components that streamline model development, deployment, monitoring, and audit readiness.

Capability Convergence, Reusability, and Self Service Enablement:

- Drive global convergence of data and AI capabilities, toolsets, engineering patterns, and operational processes.

- Reduce fragmentation by standardizing build patterns, monitoring structures, SLAs and SLOs, and change management approaches.

- Deliver reusable capability components, shared services, and repeatable patterns to maximize scale and reduce duplication.

- Enable secure, governed self service for data, analytics, and AI so teams can build on standardized capabilities with confidence.

- Ensure self service capabilities adhere to export control, global trade, data residency, and regulatory requirements.

Retire redundant services and consolidate capabilities for operational simplicity and efficiency.

Operational Excellence and Service Reliability:

- Own reliability, availability, observability, and security across all data and AI capabilities.

- Oversee global monitoring, incident management, problem management, capacity planning, disaster recovery, and lifecycle management.

- Implement strong operational controls including access, change management, operational readiness reviews, and compliance enforcement.

- Advance automation, SRE practices, and trend based operational improvements.

Collaboration and Business Enablement:

- Ensure capabilities support analytics, AI, operational workloads, transformation programs, and enterprise digital initiatives.

- Partner with Data Science and AI and Data Ontology and Governance to align capability capabilities with modeling, metadata, lineage, and quality needs.

- Support enterprise programs including SAP S4, global data products, digital transformation, engineering modernization, production systems, and sustainment operations.

Leadership and Organizational Development:

- Lead global teams of engineers, architects, SREs, capability operations professionals, and data operations specialists.

- Foster a culture of engineering excellence, operational discipline, innovation, and continuous improvement.

- Build organizational capability through workforce planning, skill development, mentoring, and global alignment.

- Strengthen collaboration across engineering, operations, and business teams.

Qualifications You Must Have:

- Bachelor’s degree in Computer Science, Management Information System, Information Technology or related technical field with a minimum of 14+ years of experience across data capabilities, data engineering, capability engineering, and capability operations; OR an advanced degree with a minimum of 12+ years of across data capabilities, data engineering, capability engineering, and capability operations.

Qualifications We Prefer:

- Experience leading large global engineering and operations organizations.

- Deep expertise in cloud based data ecosystems such as Databricks, Snowflake, and associated integration capabilities and cloud native operations.

- Experience owning AI capabilities, MLOps pipelines, model operations, and high performance compute environments.

- Strong understanding of data architecture, engineering patterns, observability, operational frameworks, and capability security.

- Proven ability to translate business strategy into technical roadmaps and deliver scalable enterprise capabilities.

- Demonstrated influence and communication skills across technical and business leadership.

- Track record of modernization, convergence, reliability engineering, and operational excellence.

- Experience building high performing engineering and operations teams.

Learn More & Apply Now:

What is my role type?

In addition to transforming the future of flight, we are also transforming how and where we work. We’ve introduced role types to help you understand how you will operate in our blended work environment.

This role is:

Remote: Employees who are working in Remote roles will work primarily offsite (from home). If you live within a reasonable commute of an RTX site with other colleagues you interact with, your manager will discuss whether there is a degree of onsite presence associated with this role.

Candidates will learn more about role type and current site status throughout the recruiting process. For onsite and hybrid roles, commuting to and from the assigned site is the employee’s personal responsibility.

*This requisition is eligible for an employee referral award.  ALL eligibility requirements must be met to receive the referral award.

As part of our commitment to maintaining a secure hiring process, candidates may be asked to attend select steps of the interview process in-person at one of our office locations, regardless of whether the role is designated as on-site, hybrid or remote.

The salary range for this role is 186,200 USD - 353,800 USD. The salary range provided is a good faith estimate representative of all experience levels. RTX considers several factors when extending an offer, including but not limited to, the role, function and associated responsibilities, a candidate’s work experience, location, education/training, and key skills.

Hired applicants may be eligible for benefits, including but not limited to, medical, dental, vision, life insurance, short-term disability, long-term disability, 401(k) match, flexible spending accounts, flexible work schedules, employee assistance program, Employee Scholar Program, parental leave, paid time off, and holidays. Specific benefits are dependent upon the specific business unit as well as whether or not the position is covered by a collective-bargaining agreement.

Hired applicants may be eligible for annual short-term and/or long-term incentive compensation programs depending on the level of the position and whether or not it is covered by a collective-bargaining agreement. Payments under these annual programs are not guaranteed and are dependent upon a variety of factors including, but not limited to, individual performance, business unit performance, and/or the company’s performance.

This role is a U.S.-based role. If the successful candidate resides in a U.S. territory, the appropriate pay structure and benefits will apply.

RTX anticipates the application window closing approximately 40 days from the date the notice was posted. However, factors such as candidate flow and business necessity may require RTX to shorten or extend the application window.

RTX is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability or veteran status, or any other applicable state or federal protected class. RTX provides affirmative action in employment for qualified Individuals with a Disability and Protected Veterans in compliance with Section 503 of the Rehabilitation Act and the Vietnam Era Veterans’ Readjustment Assistance Act.

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