Senior Software Engineer-Developer Experience

Western Governors University•Phoenix, AZ

2d•$143,700 - $222,700•Remote

About The Position

The Senior Software Engineer is responsible for the research, design, development, analysis, testing, and implementation of software operating or application systems. They communicate project information to client, project manager, or other design personnel working on projects. They maintain good working relationships with clients and staff. They write and maintains complete documentation. They support team members and ensures established goals and deadlines are met. They keep management informed of status and significant problems. Additional Job Duties Developer Experience (DevX) Design and maintain internal developer portals and golden path templates that reduce cognitive load, accelerate onboarding, and standardize how teams build, deploy, and operate services. Define and track developer productivity metrics (DORA metrics, time-to-production, developer satisfaction) to surface friction points and drive continuous platform improvement. Build self-service platform capabilities that allow product teams to provision infrastructure, configure pipelines, and deploy services without requiring platform team intervention. Partner with engineering leadership to establish and evolve the internal developer platform (IDP) strategy, ensuring it scales with organizational growth and reduces toil across teams. Port.io Administer and extend Port.io as the organization's IDP — building the software catalog, defining entity blueprints, and surfacing service health through scorecards. Implement self-service actions to automate common developer workflows (environment provisioning, dependency scaffolding, runbook execution), reducing reliance on shared platform capacity. Design scorecards to enforce engineering standards around security posture, documentation completeness, observability coverage, and production readiness. Agentic AI Design and implement multi-agent AI systems, including orchestration patterns, inter-agent communication protocols, and governance controls for autonomous workflow pipelines. Build and maintain agentic memory architectures incorporating short-term (in-context), long-term (persistent), episodic (event-sequenced), and semantic (knowledge-structured) memory patterns. Construct, query, and maintain AI knowledge graphs that enable agents to reason over structured domain knowledge and support explainable decision paths. Develop and operate Model Context Protocol (MCP) servers and clients to extend AI agent capabilities with custom tools, structured resources, and reusable prompt templates — enabling composable, governed AI integrations across product and platform surfaces.

Requirements

Understanding of the processes associated with software development, including Planning, Measurement, Coding, Testing, Reuse, Tools, Abstraction, Algorithms and Complexity, Security, and basic system understanding.
Ability to employ the tools and techniques related to an engineering discipline, such as database management, user interface development, inter-process communications, etc.
Ability to create designs that can be realized in code that achieve functional and non-functional requirements for an application or at the system level.
Appropriately uses design patterns, system decomposition, security, and fault tolerance.
A demonstrated capability in one or more design methodologies, such as Object-oriented design, Function-oriented design, data centered design and the notations appropriate for each.
Ability to understand differences, strengths and weaknesses of various Software Development Life Cycle models, and practical considerations of options
Understands implications of Software as a Service in the creation of software systems.
Thinks of and designs for scale, reliability, and cost in a public cloud environment.
Uses data and metrics to analyze Key Performance Indicators.
Ability to explain the basic value of a system and subsystems to users and how the various subsystems inter-operate to provide features.
Able to act as a partner with Operations in solving problems at a system level.
Knows what the system can and cannot do.
Ability to demonstrate a sense of urgency when looking for solutions to problems
Understands the general higher education landscape, particularly with on-line higher education, including competitive landscape, opportunities, and feature gaps.
Ability to identify innovative ideas or technologies that represent opportunities to advance the capabilities of the university education platform, our efficiencies in improving our platform, or both.
Can leverage change management processes to drive adoption.
Ability to make the team stronger and more cohesive
Strong communication skills with the ability to engage others at the right level at the right time.
Communicates effectively in group settings by knowing audience, listening effectively, and being responsive.
Presents solutions not just problems and effectively manages expectations.
Ability to identify, mitigate, or avoid risks and works closely with leads or managers to make sure that such risks and dependencies are understood, accounted, and planned for through an appropriate strategy.
Knowledge of IDP concepts including software catalog design, golden path templates, and self-service action modeling.
Ability to measure and improve developer productivity using DORA metrics, cycle time analysis, and qualitative feedback mechanisms.
Knowledge of Port.io platform capabilities — entity modeling, scorecard configuration, and self-service automation via webhooks and workflow integrations.
Knowledge of service mesh architecture and operations (Istio, Gloo Mesh), including traffic policy management and zero-trust networking patterns.
Knowledge of memory architecture patterns for AI agents: in-context management, vector store integration for long-term retrieval, episodic memory for task continuity, and knowledge graph-backed semantic memory.
Skill in implementing MCP servers that expose tools, resources, and prompt templates to AI agents in a structured, versioned, and governed manner.
Knowledge of AI agent governance: prompt injection risks, tool call authorization, output validation, and guardrail patterns for production agentic systems.
Bachelor's Degree in Computer Science, Information Technology, or related field
6 years of experience in software development; pioneering new approaches and technologies in engineering
Experience in web-based applications and web services using Java, REST, ServiceNow, and other web technologies, including experience interfacing with databases, and integrating third party products with existing infrastructure.
Equivalent relevant experience performing the essential functions of this job may substitute for education degree requirements. Generally, equivalent relevant experience is defined as 1 year of experience for 1 year of education and is the discretion of the hiring manager.

Nice To Haves

Master's Degree or PhD in Computer Science, Information Technology, or related field
Experience with IntellliJ/VS Code, JIRA, Git
Experience with Agile/Scrum Project Development
Experience with Java or a similar Object-oriented language
Experience with IDM/OSSO, Hibernate/Seam, Banner
Experience with Application Integration with legacy systems
Experience with Cloud-Native Development, and/or Porting/Refactoring of On-Site to Cloud (preferably AWS)
Experience with J2EE, Java EE, JavaScript, and SQL
Demonstrated experience building or scaling an internal developer portal with measurable adoption across multiple engineering teams.
Hands-on experience with Port.io — blueprint modeling, scorecard authoring, and CI/CD pipeline integration via self-service actions.
Production experience operating Gloo Mesh or Istio in multi-cluster environments
Demonstrated experience designing and deploying multi-agent AI systems in production, including agent role definition, orchestration topology, and failure handling.
Hands-on experience implementing MCP servers or clients to expose internal APIs or proprietary data sources to AI agents in a governed, reusable way.
Technical Certifications

Responsibilities

Acts as an expert in assigned areas of software engineering.
Mentors other more junior engineers to be more effective in their role.
Maintains accountability for quality of services in their assigned area and success of assigned projects for on-time, on-budget, and on-scope delivery.
Contributes as a lead or consultant for at least one team.
May be a ‘go-to’ person in a particular sub-discipline or application area.
Contributes formally and informally to effectiveness of the team through formal and informal mentoring and direction during team meetings and problem solving.
Communicates effectively and regularly with other disciplines to identify and resolve problems and contribute to organization success.
Leads teams or cross-functional groups in identifying and transferring knowledge through formal and informal means (formal presentations, internal white-papers, etc).
Acts as a planning consultant for team or portfolio when identifying technical risks and dependencies.
Identifies potential problems, as well as potential solutions, far in advance and mentors other engineers in risk management.
Speaks authoritatively and accurately with respect to questions related to their area of ownership or the platform as a whole.
Contributes directly, and leads others, in rapid identification of system problems minimizing time to restoration of services.
Assists engineering management in identifying opportunities for improvement within the team, including training, technical feedback, emerging problems, etc.
Applies strategies and tools to plan and execute testing strategies to find the ‘sweet spot’ that maximizes quality while minimizing costs.
Demonstrates the ‘good enough’ principle that balances quality and time to implement.
Interprets functional, non-functional, and implied requirements into designs and code that meet those specifications.
Identifies gaps, risks, and deficiencies in such requirements and proposes solutions.
Guides more junior engineers on how to plan and execute on requirements delivery.
Performs other job-related duties as assigned.
Design and maintain internal developer portals and golden path templates that reduce cognitive load, accelerate onboarding, and standardize how teams build, deploy, and operate services.
Define and track developer productivity metrics (DORA metrics, time-to-production, developer satisfaction) to surface friction points and drive continuous platform improvement.
Build self-service platform capabilities that allow product teams to provision infrastructure, configure pipelines, and deploy services without requiring platform team intervention.
Partner with engineering leadership to establish and evolve the internal developer platform (IDP) strategy, ensuring it scales with organizational growth and reduces toil across teams.
Administer and extend Port.io as the organization's IDP — building the software catalog, defining entity blueprints, and surfacing service health through scorecards.
Implement self-service actions to automate common developer workflows (environment provisioning, dependency scaffolding, runbook execution), reducing reliance on shared platform capacity.
Design scorecards to enforce engineering standards around security posture, documentation completeness, observability coverage, and production readiness.
Design and implement multi-agent AI systems, including orchestration patterns, inter-agent communication protocols, and governance controls for autonomous workflow pipelines.
Build and maintain agentic memory architectures incorporating short-term (in-context), long-term (persistent), episodic (event-sequenced), and semantic (knowledge-structured) memory patterns.
Construct, query, and maintain AI knowledge graphs that enable agents to reason over structured domain knowledge and support explainable decision paths.
Develop and operate Model Context Protocol (MCP) servers and clients to extend AI agent capabilities with custom tools, structured resources, and reusable prompt templates — enabling composable, governed AI integrations across product and platform surfaces.