Staff AI and Productivity Engineer

Role Description

As a $1B publicly traded SaaS company operating in a rapidly evolving technology landscape, Workiva is seeking a Staff AI & Productivity Engineer to lead the design, deployment, and scaling of our enterprise AI capabilities. This role sits at the intersection of AI engineering and employee productivity, with a mission to make AI tools genuinely useful for the people of Workiva.

You will serve as the lead technical practitioner for our AI and collaboration platforms, building intelligent integrations and automated workflows that measurably improve how employees work. You are a hands-on engineer with a product mindset, the technical depth to build at the code level, and the business instincts to prioritize what matters most.

What You'll Do

• Build and operationalize AI-driven tools including custom Slack agents, automated knowledge-retrieval systems, and intelligent workflow triggers using Claude, Gemini, OpenAI, MCP servers, and related APIs.
• Configure and manage AI endpoints and LLM integrations directly, including MCP server development, prompt engineering, API configuration, and performance tuning.
• Move quickly from proof-of-concept to production-ready tooling, taking a hands-on approach to prototyping and rapid iteration.
• Partner with stakeholders across the company to uncover root-cause friction and engineer specific solutions that deliver long-term productivity value.
• Engineer and maintain integrations between enterprise systems using Workato and API-based automation, with a focus on AI-augmented workflows.
• Serve as subject matter expert for our productivity stack (Google Workspace, Slack, Zoom), performing advanced configuration and complex integration work.
• Architect technical guardrails and governance practices that balance enterprise security with a frictionless employee experience.
• Design modular, repeatable integration patterns that allow the environment to be managed with precision across global teams.
• Perform deep-dive technical audits of SaaS utilization to identify and execute cost optimization and system rationalization opportunities.
• Own the AI enablement product lifecycle alongside the product owner, including roadmap input, feature delivery, stakeholder communication, and vendor alignment.
• Provide technical mentorship and guidance to team members, championing AI-forward practices and upskilling the team on emerging tools and architectures.

Qualifications

• 6+ years of experience in systems engineering, technical implementation, or a related engineering field within a high-growth SaaS environment.
• Practical experience implementing AI tools at the code level: API configuration, prompt engineering, and integrating LLMs into existing software ecosystems.
• Hands-on experience with MCP (Model Context Protocol) server development and deployment.
• Experience building production AI agents or agentic workflows using Claude, OpenAI, or Gemini APIs.
• Familiarity with enterprise security and governance requirements for AI tooling, including data classification and access controls.
• Strong proficiency in Python with deep understanding of REST APIs, webhooks, and modern integration patterns.
• Demonstrated experience building multi-step, logic-heavy automations using platforms like Workato or equivalent.
• Working knowledge of Google Workspace, Slack Enterprise, and Zoom administration and configuration.

Preferred Qualifications

• Experience in a technical product owner or platform engineering lead capacity.
• Strong interpersonal and communication skills, with the ability to translate complex technical concepts for non-technical stakeholders.
• Ability to operate with direction from broad objectives, self-identifying technical gaps and building the solutions to close them.
• Technical writing experience and a track record of building institutional knowledge through documentation.

Requirements

• Minimal (<10%) travel for team jams or engineering wide conferences.
• Reliable internet access for remote working opportunities.

Benefits

• Salary range in the US: $129,000.00 - $207,000.00.
• A discretionary bonus typically paid annually.
• Restricted Stock Units granted at time of hire.
• 401(k) match and comprehensive employee benefits package.