Senior AI Cloud Engineer

About this role

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, Clo

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