Senior Software Engineer - AI Enablement

ISU Research Park; Ames, Northern (IA, KY); Hybrid; USD 110,000 - 160,000; Full time

Job summary

ISU Research Park seeks a Senior Software Engineer to lead AI Enablement initiatives, owning a domain such as the MCP ecosystem and AI agent deployment. You will integrate tools and ensure secure, scalable implementations across the PDLC.

You will build, deploy, and refine AI-enabled infrastructure, while documenting best practices and mentoring peers for higher velocity and quality in a cutting-edge technology stack.

Qualifications

• 4+ years of related software development experience.
• Strong proficiency in back-end services, proxy servers, and API integrations.
• Experience with Python, Go, or TypeScript preferred.
• Extensive experience using AI-augmented IDEs (Cursor, Claude Code).
• Ability to translate complex technical implementations into clear documentation for the engineering org.

Responsibilities

• Own a specific technical domain (e.g., MCP server infrastructure) and be the primary maintainer.
• Architect and maintain internal MCP servers and deploy cloud-hosted autonomous agents.
• Deliver software solutions with sustainable, reusable, and scalable code at milestones.
• Evaluate emerging AI tools to ensure compatibility with architecture and security standards.
• Document best practices, creating playbooks to standardize AI usage and reduce KTLO.
• Provide tactical consulting to product teams for AI agent integrations and troubleshoot blockers.
• Monitor metrics to measure AI impact on velocity and code quality.
• Mentor team members on AI-augmented development techniques and reviews.

Skills

Back-end services

API integrations

Python

Go

TypeScript

AI-augmented IDEs

Technical communication

Tools

Cursor

Claude Code

Job description

Senior Software Engineer - AI Enablement

As a Senior Software Engineer , you will be the technical engine of the AI Enablement team. Your mission is to bridge the gap between \"AI-adjacent\" and \"AI-native\" by building the tools and integrations that make AI indispensable to the PDLC. While you will contribute across our entire stack, you will be expected to own a specific domain—such as our Model Context Protocol (MCP) ecosystem, wk-ai-prototyping repo or our future automated testing agents—becoming the go-to expert for that area while maintaining the flexibility to support the broader team.

Key Responsibilities

Architecture & Technical Mastery (Primary Focus)

Domain Ownership: Take deep ownership of a specific technical domain (e.g., our MCP server infrastructure or wk-ai-prototyping repo). Be the primary maintainer and visionary for this component.

Build & Deploy: Architect and maintain internal MCP servers (integrating Jira, Splunk, Datadog, etc.) and deploy cloud-hosted autonomous agents within FedRAMP boundaries.

Resilient Implementation: Independently deliver software solutions through a set of milestones, ensuring code is sustainable, reusable, and optimized for an AI-augmented environment.

Tooling Evaluation: Conduct deep technical spikes on emerging AI tools (e.g., Qodo, Cursor, Claude Code) to ensure compatibility with Workiva’s architecture and security standards.

Process Integration & Consulting (Growth Path)

Best Practice Documentation: Actively surface and document \"Golden Paths\"—creating playbooks that standardize how engineers utilize AI to reduce KTLO (Bugfixes, CVEs, Migrations).

Light Consulting: Serve as a tactical consultant for product teams, helping them integrate AI agents into their specific workflows and troubleshooting technical blockers.

Data-Driven Quality: Implement and monitor metrics (using tools like Mstone) to measure the impact of AI on team velocity and code quality.

Skill Mastery: Level up team members by providing guidance on AI-augmented development techniques and conducting \"Review-First\" code reviews.

Cultural Catalyst: Showcase successful use cases and strategic wins in engineering syncs to encourage organic AI adoption.

Minimum Qualifications

Experience: 4+ years of related software development experience.

Technical Stack: Strong proficiency in back-end services, proxy servers, and API integrations. Experience with Python, Go, or TypeScript is preferred.

AI Literacy: Extensive experience using AI-augmented IDEs (e.g., Cursor, Claude Code) to maintain high throughput and quality.

Communication: Ability to translate complex technical implementations into clear, actionable documentation for the broader engineering org.