Plains is an industry-leading transportation and midstream provider specializing in transportation, storage, processing and marketing solutions for crude oil. We own an extensive network of pipeline transportation, terminalling, storage and gathering assets in key oil producing basins and transportation corridors and at major market hubs in the United States and Canada. The company is headquartered in Houston, Texas.

We’re on the lookout for passionate self‑starters who thrive in fast‑moving, collaborative, and innovative environments.

The Senior Advisor, AI Engineering is responsible for designing, building, and guiding the implementation of custom AI enabled solutions, with a strong emphasis on Retrieval Augmented Generation, agent style orchestration, and integration with enterprise platforms. The role partners closely with Platform teams and Product Owners to shape solution designs, technical patterns, and delivery approaches for AI driven capabilities.

Deep prior AI or LLM experience is not required. Strong software engineering fundamentals, architectural thinking, and the ability to guide others through complex technical decisions are more important.

Key Responsibilities

Applied AI Architecture and Solution Design

Lead the technical design of AI enabled applications that support enterprise business workflows, including copilots, assistants, and intelligent automations.

Define and apply standard patterns for Retrieval Augmented Generation, including data ingestion, chunking strategies, embeddings, vector indexing, retrieval logic, and grounding techniques.

Design orchestration approaches for AI applications, including tool calling, agent workflows, and MCP style integrations to enterprise systems and services.

Partner with Platform teams to ensure AI solutions align with enterprise architecture, security, data governance, and cloud standards.

Act as a technical advisor to Product Owners, helping translate business intent into feasible, scalable solution designs.

Software Engineering and Integration

Build and maintain backend services and APIs, primarily using Python, that support AI applications and integrations.

Guide implementation decisions to ensure solutions are secure, scalable, performant, and maintainable in production environments.

Review designs and code for AI solutions developed within the team, providing technical direction and setting engineering quality standards.

Balance rapid experimentation with disciplined engineering practices to move solutions from prototype to production.

Data and Platform Integration

Design integration patterns between AI applications and structured and unstructured enterprise data sources, including SQL based systems, lakehouse platforms, and document repositories.

Collaborate with data engineers and platform teams to ensure data products are fit for AI workloads and aligned with governance requirements.

Advise on tooling and platform choices, including Azure AI services and Databricks Apps, based on solution needs and enterprise constraints.

Governance, Ethics & Risk Management

Design and implement responsible AI principles, including fairness, transparency, explainability, and privacy‑by‑design to be adopted by both platform and enterprise.

Partner with IS and Risk stakeholders to create policies to ensure AI solutions comply with internal policies, regulatory requirements, and ethical standards.

Lead AI governance forums, design reviews, and risk assessments as required.

Collaboration & Continuous Improvement

Serve as a senior technical voice within the applied AI practice, shaping standards, design patterns, and reusable components.

Mentor and guide other engineers, helping raise overall engineering and AI application maturity.

Facilitate technical discussions across teams, helping stakeholders navigate tradeoffs related to architecture, risk, cost, and delivery timelines.

Stay current with applied AI and software engineering trends, translating emerging patterns into practical guidance for the organization.

Required Qualifications

Education

Bachelor’s degree in Computer Science, Engineering, Data Science, Mathematics, or a related field, or equivalent practical experience.

Advanced degree is considered an asset.

Experience

Senior level experience in software engineering roles, with a demonstrated track record of designing and delivering production grade systems.

Experience leading or influencing technical design decisions across complex solutions, including partnering with platform, architecture, or product teams.

Hands on experience building backend services and APIs that support business critical applications.

Experience translating ambiguous business needs into scalable technical solutions, and guiding delivery from concept through production.

Experience operating in enterprise environments with cloud platforms, security constraints, and data governance considerations.

Technical Skills

Strong proficiency in Python, with experience building and maintaining backend services and APIs.

Experience working in cloud environments, preferably Azure, though experience with other major cloud providers is transferable.

Experience integrating applications with structured and unstructured data sources, including SQL based systems and modern data platforms.

Familiarity with applied AI patterns such as Retrieval Augmented Generation, embeddings, vector search, or agent style orchestration.

Bonus experience with Databricks, Spark, or data engineering concepts such as pipelines and lakehouse architectures.

Knowledge & Competencies

Strong software engineering fundamentals, including system design, architecture patterns, and production readiness.

Ability to act as a technical advisor, guiding Product Owners and stakeholders through design decisions, tradeoffs, and sequencing.

Comfort partnering with platform, data, and security teams to ensure solutions align with enterprise standards.

Strong problem-solving skills and ability to operate effectively in ambiguous, fast evolving problem spaces.

Clear communicator who can explain complex technical concepts to both technical and non‑technical audiences.

Demonstrated ability to mentor other engineers and positively influence technical practices across a team.

Preferred Qualifications

Experience with large‑scale data platforms, data lakes, or streaming data architectures.

Experience supporting AI solutions in regulated or risk‑sensitive environments.

Exposure to optimization, forecasting, or decision‑support models.

Experience working in agile or product‑oriented delivery models.

Requirements:

Cleared criminal history (background) and satisfactory reference checks

Compliance with the Company’s drug and alcohol policy including pre-employment D&A testing.

This position is not eligible for employment-based visa sponsorship. Applicants must be authorized to work in the U.S. for the duration of their employment

#Plains

At Plains, our employees are our most valuable asset. Hard work is rewarded with competitive compensation and a top-tier benefits program designed to keep our employees safe, healthy and happy. We work hard to deliver the best results to our stakeholders, and we also respect our employees' need for personal and family time, which is reflected in our benefits program .

We are proud to be an Equal Opportunity Employer . We are committed to providing employment opportunities to all qualified individuals, without regard to age, race, color, national or ethnic origin, religion, sex, sexual orientation, gender identity or expression, veteran status, genetic information, disability, or any other characteristic protected by federal, state, or local law. Applicants with disabilities can request accessible formats, communication supports, or other accessibility assistance by contacting WebCareers@Plains.com .

Salary details estimated by job boards such as Indeed, Glassdoor, and LinkedIn do not represent Plains’ compensation structure. We thank all candidates for their interest; however, only those selected for an interview will be contacted.

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