Senior AI Enablement Engineer — Domain Lead

Workiva; United States; On-site; USD 111,000 - 180,000; Full time

Benefits offered by this job

Discretionary bonus

Restricted Stock Units

401(k) match

Comprehensive benefits package

Job summary

Workiva is seeking a Senior Software Engineer to drive AI Enablement within a hands-on, domain-focused role. You will own critical components such as MCP infrastructure, integrate Jira, Splunk, and Datadog, and deploy autonomous agents within FedRAMP boundaries.

You’ll advance best practices, help product teams adopt AI agents, and measure impact on velocity and quality through data-driven metrics, while mentoring colleagues and sharing knowledge across engineering.

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.
• AI literacy with AI-augmented IDEs (e.g., Cursor, Claude Code).
• Ability to translate complex technical implementations into clear documentation for the team.

Responsibilities

• Domain Ownership: take deep ownership of a specific technical domain (e.g., MCP server infrastructure or wk-ai-prototyping repo).
• Build & Deploy: architect and maintain internal MCP servers and deploy cloud-hosted autonomous agents within FedRAMP boundaries.
• Resilient Implementation: deliver software solutions with sustainable, reusable code.
• Tooling Evaluation: spike emerging AI tools to ensure compatibility with Workiva’s architecture and security standards.
• Process Integration: document golden paths and act as a tactical consultant for product teams to integrate AI agents into workflows.

Skills

Backend services

Proxy servers

API integrations

Python

Go

TypeScript

AI-augmented IDEs

Communication

Job description

Workiva is seeking a Senior Software Engineer to drive AI Enablement within a hands-on, domain-focused role. You will own critical components such as MCP infrastructure, integrate Jira, Splunk, and Datadog, and deploy autonomous agents within FedRAMP boundaries.

You’ll advance best practices, help product teams adopt AI agents, and measure impact on velocity and quality through data-driven metrics, while mentoring colleagues and sharing knowledge across engineering.