Staff AI and Productivity Engineer

Role Overview

• 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

Requirements

• 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

Tech Stack

• Python

Benefits

• A discretionary bonus typically paid annually
• Restricted Stock Units granted at time of hire
• 401(k) match and comprehensive employee benefits package