Arizona State University

Senior AI Cloud Engineer

Arizona State University$140K — $168K *
Education, Government & Non-Profit
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's degree with 7 years of relevant experience or equivalent combination of education and experience.
  • Hands-on experience with MCP servers and AI integrations.
  • Strong understanding of the Model Context Protocol and its components.
  • Experience using AWS cloud services and serverless architectures.
  • Proficiency in Node.js and modern frontend frameworks like React.

Responsibilities

  • Design, build, and maintain production-grade MCP servers.
  • Implement secure access for AI applications to essential resources.
  • Develop reusable MCP templates and SDK wrappers for ASU teams.
  • Integrate MCP services with ASU's existing AI applications.
  • Design scalable cloud architectures using AWS-native services.

Benefits

  • Hybrid work environment with flexible scheduling options.
  • Collaborative and team-oriented work culture.
  • Opportunities for professional development and skills training.
  • Engagement with innovative AI projects in education.
  • Supportive work environment committed to inclusion and belonging.
Full Job Description
Job Profile:
Applications Developer 4

Job Family:
IT Applications

Time Type:
Full time

Apply before 11:59 PM Arizona time the day before the posted End Date.

Minimum Qualifications:
Bachelor's degree and seven (7) years of experience appropriate to the area of assignment/field; OR, Any equivalent combination of experience and/or training from which comparable knowledge, skills and abilities have been achieved.

Job Description:

Arizona State University is seeking a Senior Software Engineer, MCP / Full-Stack AI Platform Engineer to join the AI Acceleration Team within Enterprise Technology. This role will help design, build, and scale the technical infrastructure that enables ASU's next generation of AI-powered learning, research, and operational tools. The engineer will focus on the Model Context Protocol (MCP), which connects AI applications to external tools, data sources, workflows, and enterprise systems in a secure, governed way. The successful candidate will serve as a senior technical contributor and architecture partner for ASU's AI platform ecosystem, including CreateAI, ASU's secure, model-agnostic AI platform. This person will build production-grade MCP servers, full-stack AI-enabled applications, APIs, AWS infrastructure, data integrations, and reusable patterns that help ASU safely connect AI systems to university services. This is a hands-on engineering role for someone who is comfortable moving between architecture, backend development, frontend development, cloud infrastructure, security design, and stakeholder collaboration. The ideal candidate is technically deep, product-minded, mission-driven, and excited to help ASU build tools for the future of learning. The AI Acceleration Team is responsible for helping ASU build, govern, and scale responsible AI capabilities across the institution. This role will help the team in building secure, agentic, tool-connected AI systems that can support meaningful university workflows.

The team supports ASU's AI strategy by:
  • Building and maintaining secure AI infrastructure and platforms, including CreateAI
  • Developing AI-powered tools that support learners, faculty, researchers, and staff
  • Creating reusable patterns for responsible AI development
  • Supporting enterprise integrations between AI systems and university data/services
  • Partnering across ASU to build culture, literacy, trust, and responsible adoption around AI
  • Advancing ASU's vision for the future of learning through personalized, ethical, and accessible AI experiences


Salary Range: $140,000- $168,100/ Depends on Experience

Essential Duties:

MCP Platform Engineering
  • Design, build, deploy, and maintain production-grade MCP servers and clients.
  • Implement MCP capabilities that allow AI applications to securely access approved tools, resources, prompts, and enterprise data.
  • Develop reusable MCP templates, SDK wrappers, reference services, and starter patterns for ASU engineering teams.
  • Integrate MCP-enabled services with CreateAI and other ASU AI applications.
  • Track the evolving MCP specification and recommend updates to ASU implementation patterns.
  • Evaluate emerging agentic interoperability standards beyond MCP and advise on practical adoption.


Full-Stack AI Application Development
  • Build full-stack applications and platform features that support AI-enabled workflows.
  • Develop backend services, REST APIs, serverless functions, frontend interfaces, and integration layers.
  • Work with modern JavaScript/TypeScript frameworks such as React or Next.js.
  • Develop backend services in Python, Node.js, or comparable languages.
  • Implement secure user experiences that make complex AI capabilities accessible to non-technical users.
  • Rapidly prototype AI-driven experiences, validate usability, and mature successful prototypes into reliable production systems.


AWS Cloud Architecture and Infrastructure
  • Design and implement AWS-native services using technologies such as:
    • Lambda
    • API Gateway
    • S3
    • DynamoDB
    • CloudFront
    • SQS/SNS
    • EventBridge
    • CloudWatch
    • Secrets Manager
    • OpenSearch
    • Bedrock
  • Build infrastructure-as-code using Terraform or comparable tools.
  • Design scalable, resilient, cost-conscious cloud architectures.
  • Implement deployment pipelines, CI/CD workflows, automated testing, and operational monitoring.
  • Troubleshoot performance, reliability, security, and cost issues in production systems.


Security, Governance, and Responsible AI
  • Partner with security and operations teams to define guardrails for MCP and AI integrations.
  • Help assess risks such as:
    • Prompt injection
    • Tool poisoning
    • Data exfiltration
    • Over-permissioned tools
    • Supply-chain vulnerabilities
    • Insecure third-party MCP servers
    • Sensitive data exposure
  • Implement authentication and authorization using OAuth, OIDC, JWTs, scopes, service roles, and secrets management.
  • Ensure AI integrations follow ASU expectations for privacy, FERPA-aware design, responsible innovation, and human-centered impact.
  • Build logging, auditing, and usage analytics into MCP and AI services.
  • Contribute to integration review processes and technical approval criteria.


Desired Qualifications:
  • Hands-on experience designing, building, or operating MCP servers, MCP clients, AI tools, or agentic AI integrations.
  • Strong understanding of the Model Context Protocol, including tools, resources, prompts, transports, and security considerations.
  • Experience with retrieval-augmented generation, embeddings, vector search, prompt engineering, evaluation, and agentic workflows.
  • Familiarity with AI safety, responsible AI practices, model evaluation, and governance.
  • Experience with Node.js and modern frontend frameworks such as React
  • Experience designing RESTful APIs, event-driven services, and microservice-style architectures.
  • Experience with AWS cloud services, especially serverless architectures (AWS Lambda, API Gateway, S3, DynamoDB, IAM, CloudWatch, CloudFront, SQS)
  • Strong background in API security, authentication, authorization, and secrets management, including OAuth, OIDC, and JWT.
  • Experience supporting security reviews, incident response, threat modeling, or integration approval processes.
  • Ability to explain complex technical concepts clearly to technical and non-technical audiences.
  • Strong written communication, documentation, and presentation skills.
  • Demonstrated ability to model empathy, compassion, and emotional intelligence.
  • Experience in a values-driven organization with a strong commitment to inclusion and belonging.
  • Ability to cultivate a psychologically safe environment where all team members can thrive.
  • Capacity to inspire and drive meaningful change in individual, institutional, and corporate behaviors to support a more sustainable environment.
  • Commitment to leading by example through effective communication, active participation, and advocacy for the institution's sustainability programs.


Special Instructions:

In your cover letter, please describe your experience using artificial intelligence (AI), including the tools or technologies you have worked with. We also encourage you to share your passion for AI and how you have applied it to improve your work, solve problems, increase efficiency, or support innovation.

Working Environment
  • Activities are primarily performed in an environmentally controlled office or hybrid work setting.
  • Work requires regular use of a computer, keyboard, mouse, video conferencing, and collaboration tools.
  • Role may require extended periods of sitting and focused technical work.
  • Regular communication with team members, stakeholders, and university partners is required.
  • Responsibilities may require changing priorities quickly, responding to production issues, and resolving ambiguity across teams.


Driving Requirement:
Driving is not required for this position.

Location:
Off-Campus: Scottsdale

Funding:
No Federal Funding

Instructions to Apply:

Current employees, student workers seeking staff opportunities, and students applying for student worker positions must apply directly through the Workday Jobs Hub.

Please use the link below to log in using single sign-on.
https://www.myworkday.com/asu/d/inst/1$9925/9925$25702.htmld

To be considered, your application must include all of the following attachments:
  • Cover letter
  • Resume or CV


Multiple documents may be uploaded in the attachments section. Alternatively, applicants may combine all required materials into a single PDF for submission. Please ensure uploaded documents are clearly labeled and include your name.

Please ensure your resume includes all employment information in month and year format, for example 6/04 to 8/14, along with job title, job duties, and employer name for each position. Your resume should clearly demonstrate how your experience and background meet the minimum and desired qualifications for this position. Incomplete applications or missing required materials may not be considered.

Important: Do not withdraw your application to make edits. Once an application is withdrawn, it cannot be edited, reactivated, or replaced with a new submission. If you have questions or need assistance, please contact The Office of Human Resources Talent Acquisition before the posting close date.

Graduate Assistant, Intern and part-time positions are counted as half time for experience equivalency, meaning one year equals six months of experience.

Only electronic applications will be accepted for this position. By submitting an application, you confirm that the information provided is accurate and complete.

About Arizona State University

Arizona State University (ASU) is a public research university with its main campus in Tempe, Arizona. It is one of the largest public universities in the United States by enrollment. ASU offers degree programs in more than 800 areas of study, including over 250 undergraduate majors and more than 120 graduate programs. ASU is classified among "R1: Doctoral Universities ? Very high research activity". ASU's athletic teams are called the Sun Devils and compete in the Pac-12 Conference. ASU has multiple campuses throughout the Phoenix metropolitan area, with four regional campuses and several extension centers.
Learn more about Arizona State University
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