Principal Engineer, AI & Emerging Technology

About the Role

The Principal/Sr. Engineer of AI and Emerging Technology will support the coordination, selection, pilot testing, evaluation, integration/adoption, and maintenance of artificial intelligence (AI) and related emerging technologies into Targa’s operational work processes. This role partners closely with third-party investment teams to review startups and partners, perform technical diligence, design and execute pilots, and shape co-development opportunities where strategic investments enable Targa to influence product direction. Sitting within the Engineering Services organization, this role collaborates with Information Technology, Enterprise Asset Management (EAM), Reliability, Rotating Equipment Specialists, Mechanical Integrity (MI), Corrosion, OT/SCADA, Pipeline Integrity, Operations, Engineering, and Commercial teams to ensure efficient and impactful adoption of AI and Emerging Technology across the enterprise.

Responsibilities

• Lead identification, prioritization, and piloting of new technologies, including AI/ML, digital twins, generative AI, equipment upgrades, and autonomous inspection technologies across operational assets.
• Maintain a prioritized backlog of AI and Emerging Technology use cases mapped to organizational KPIs (e.g., corrosion growth rates, MTBF for rotating equipment).
• Partner with SCADA and Measurement teams to build reliable real-time data pipelines for AI and Emerging Technology model deployment.
• Coordinate with internal and external resources to develop, test, and deploy AI/ML models.
• Provide tracking and regular updates on testing progress; interface with testing groups to maintain strong communication and clear issue/decision logs.
• Support investment partners in scouting startups and technology partners; translate business pain points into technical needs, screen solutions, and maintain a pipeline of high-potential opportunities.
• Lead technical diligence for venture and partner opportunities to inform investment and partnership decisions.
• Define pilot/POC scope, success criteria, test plans, and measurement approaches; run disciplined stage-gates from prototype through field pilot to scale decision.
• Own day-to-day technical partnership execution during pilots and post-investment, ensuring successful handoff into steady-state operations.
• Drive structured feedback loops with startups/partners to influence product roadmaps and co-development aligned to Targa standards.
• Partner with IT/OT and platform teams to operationalize MLOps practices.
• Establish and track KPIs and cost/benefit analyses for AI and Emerging Technology initiatives; present findings to senior leadership.
• Support change management and training efforts to improve AI and Emerging Technology literacy across the organization.
• Drive cultural adoption of AI/Emerging Technology through rapid prototyping and feedback loops.
• Conduct field visits to evaluate technology adoption and identify improvement opportunities.
• Serve as SME for monitoring, maintenance, and continual development of deployed technologies.

Qualifications

• Bachelor’s degree in Engineering, Computer Science, Data Science, or related field (or equivalent industry experience).
• 7+ years of experience in midstream oil & gas or industrial operations with a focus on operations, technology, or innovation.
• Proven experience deploying AI/ML solutions in operational environments.
• Strong understanding of Operating Equipment, SCADA, Maximo, Measurement, and asset performance systems.
• Excellent communication, leadership, and decision-making skills.
• Ability to travel frequently and respond to urgent matters outside standard business hours.
• Familiarity with regulatory frameworks (DOT/PHMSA, EPA, OSHA) and how AI & Emerging Technology can support compliance and performance.
• Familiarity with pipeline, compressor, gas plant, and fractionator operations and how AI & Emerging Technology can enhance performance.

Preferred Qualifications

• Vision to see future possibilities with the knowledge to understand deployment limitations.
• Field engineering and operational background.
• Experience working with startups/partners, including scouting, evaluation, pilots/POCs, and scale-up.
• Experience supporting investment diligence by translating technical findings into clear decision inputs for business stakeholders.
• Experience designing testing and acceptance strategies for new technology deployments.
• Ability to define and track KPIs/value realization for pilots and deployments.
• Strong vendor/partner evaluation skills, including reviewing architectures, security posture, and operational requirements.
• Working knowledge of data/AI and automation tooling (e.g., Python, APIs, cloud/edge platforms) and concepts like model governance and system integration.