Senior Software Engineer

Job Type:

Regular

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 Software Engineer 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.

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