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