Principal Engineer I - AI Engineering

Western Alliance Bank•Phoenix, AZ

About The Position

The Principal Engineer I - AI Engineering provides subject-matter expertise and technical ownership for enterprise GitHub Copilot and agentic software engineering capabilities. The role defines and evolves the technical vision, architecture, engineering patterns, governance, and capabilities of the enterprise Agentic SDLC Harness, including reusable agents, skills, instructions, rules, plugins, MCP integrations, and other AI-assisted engineering capabilities. It partners with Development, Architecture, DevOps, Quality Engineering, Security, Cloud, Governance, project sponsors, platform owners, engineering teams, and technology leaders to build a secure, scalable, reliable, compliant, and supportable ecosystem that accelerates software delivery while maintaining engineering standards and controls. The position provides strategic engineering leadership across organizational boundaries, influences standards and architecture decisions, communicates complex concepts to technical and leadership audiences, and mentors engineers in GitHub Copilot, agentic engineering, DevOps, and related practices. It also translates emerging technology into enterprise-ready solutions, establishes adoption and operating practices, and maintains technical architecture and engineering documentation.

Requirements

At least 8 years of progressive software engineering, platform engineering, DevOps, developer enablement, or related IT experience, including at least 5 years designing, engineering, administering, or supporting enterprise development platforms.
Bachelor's degree in computer science, information technology, engineering, systems analysis, or a related field.
Deep understanding of modern software engineering practices, SDLC processes, source control, CI/CD, developer tooling, and platform engineering.
Hands-on experience engineering, administering, and supporting enterprise development platforms, including GitHub Enterprise; experience with Azure DevOps is preferred.
Experience with repository governance, identity and access, integrations, policies, CI/CD, and developer tooling.
Demonstrated hands-on experience with GitHub Copilot and AI-assisted software engineering, including enterprise configuration, agentic capabilities, customization, integration, governance, and developer enablement.
Experience architecting enterprise developer platforms and developer enablement ecosystems, including reusable frameworks, integrations, automation, engineering patterns, and shared platform capabilities.
Strong understanding of generative AI and agentic architectures, including AI agents, tool calling, agent orchestration, prompt engineering, context engineering, retrieval patterns, human-in-the-loop controls, and secure integration with enterprise systems.
Experience designing security and governance controls for AI-assisted engineering, including identity and access, least-privilege tool access, secrets and sensitive-data protection, repository permissions, third-party integrations, MCP servers, and agent/tool execution boundaries.
Software engineering experience and ability to design, build, test, and maintain automation, integrations, developer tooling, APIs, scripts, and reusable engineering components.
Ability to translate emerging technologies into secure, scalable, and supportable enterprise solutions.
Ability to work effectively in a team environment.
Advanced knowledge of enterprise architecture, technology governance, security and risk frameworks, and integrating new capabilities into existing enterprise platforms and operating models.
Advanced speaking and writing communication skills.
Advanced knowledge of applicable regulatory and legal compliance obligations, rules and regulations, industry standards, and practices.

Nice To Haves

Master's degree or MBA in a related field.
Experience working in a regulated financial-services environment and supporting technology risk assessments, audits, regulatory examinations, and control-evidence requests.
Previous technical leadership experience.
Experience with Azure DevOps.

Responsibilities

Serve as the enterprise technical owner and subject-matter expert for GitHub Copilot and AI-assisted software engineering.
Define the technical strategy, architecture, standards, configuration model, and operating model for enterprise GitHub Copilot and agentic software engineering.
Engineer, configure, and evolve enterprise GitHub Copilot capabilities, including managed settings, policies, model availability, custom agents, skills, instructions, rules, plugins, approved MCP servers, and related extensibility.
Evaluate new GitHub Copilot and agentic engineering capabilities through controlled testing and experimentation, and determine enterprise readiness, security and governance requirements, adoption strategy, implementation approach, and business value.
Design and evolve the enterprise Agentic SDLC Harness, including patterns for orchestration, tool access, context management, permissions, and human oversight.
Design and implement technical guardrails for AI-assisted engineering, covering access controls, approved tools and models, MCP server permissions, agent capabilities, repository interactions, data handling, and enterprise security, regulatory, compliance, and risk requirements.
Establish lifecycle management practices for configurations, including source control, peer review, testing, approval, versioning, staged deployment, promotion across test and enterprise environments, and rollback.
Serve as a technical escalation point for complex Copilot and agentic engineering issues, including configuration, authentication, IDE integration, policy enforcement, agent and plugin behavior, MCP integrations, and platform interoperability.
Establish monitoring and operational practices for platform availability, configuration health, integration reliability, usage, and emerging technical risks.
Develop reference implementations, technical standards, engineering patterns, playbooks, reusable examples, quick-start guides, and enablement materials to support safe adoption.
Define and monitor enterprise metrics for adoption, usage, developer experience, quality, reliability, engineering effectiveness, and value realization, and use insights to improve the platform and developer productivity.
Communicate platform roadmap, adoption, risk, technical health, and value realization to engineering and technology leadership.
Maintain enterprise technical architecture and engineering documentation, including reference architectures, integration patterns, configuration standards, security models, decision records, support procedures, and operational runbooks.
Partner with engineering, architecture, DevOps, quality, security, cloud, and governance teams to refine requirements and drive solutions from concept through enterprise adoption.
Provide technical leadership, influence engineering standards and architectural decisions, communicate complex technical concepts, and mentor engineers.