Staff Software Engineer - AI Platform

CaptivateIQ is transforming the way companies plan, manage, and optimize sales performance. We started by revolutionizing incentive compensation management, and now we're expanding our platform to solve broader sales planning challenges. Recognized by industry analysts like Forrester and G2 and backed by top-tier investors, including Sequoia, ICONIQ, Accel, and Sapphire Ventures,  we empower high-growth companies like Netflix, Figma, and Stripe with the flexibility and insights needed to drive revenue performance.   About the Role

CaptivateIQ is building AI capabilities that will transform how enterprises manage sales performance. We're looking for a **Staff Software Engineer** to set the technical strategy for our Agentic SDK team, an internal developer platform that enables product teams across the company to build AI-powered features.

This is a strategic technical leadership role with multi-year, multi-team scope. You'll define the architecture and technical direction for AI at CaptivateIQ, making decisions that have no clear answer and partnering with senior Engineering, Product, and Design leadership to shape our long-term vision. You'll be responsible for technical choices that affect the entire organization, from platform design to engineering-wide quality standards.

As the technical anchor on a small, high-impact team, you'll lead by influence across organizational boundaries. You'll drive alignment between product teams consuming the Agentic SDK and the platform capabilities we build. You'll establish the bar for engineering excellence and invest deeply in coaching P4 engineers toward staff-level impact.

This is a rare greenfield opportunity to define how AI gets built at a growing enterprise software company. You'll shape not just the technology, but the culture and practices that scale with the organization.

Job Location The candidate selected for this opportunity must reside near one of the following locations:   Hybrid (in-office 3 days per week) Austin, TX   Remote Raleigh, NC  Nashville, TN  Toronto, Canada  

Responsibilities

• Set the multi-year technical strategy for AI platform development, partnering with senior EPD leadership on long-term vision
• Architect foundational AI systems that serve multiple product teams, including LLM orchestration frameworks, MCP infrastructure, and agent patterns
• Own technical decisions with organization-wide impact where the right answer is ambiguous or contested
• Define engineering-wide quality standards and best practices for AI development, establishing patterns that scale across teams
• Drive technical alignment across the Agentic SDK team and product teams consuming AI capabilities
• Invest deeply in coaching P4 engineers, helping them develop toward staff-level scope and strategic thinking
• Represent CaptivateIQ's technical perspective in industry discussions, open-source contributions, or technical publications

Requirements

• 8+ years of professional software engineering experience with demonstrated progression into staff-level technical leadership
• Deep expertise in LLM orchestration: production experience building agent frameworks, including agent design patterns, tool integration, and workflow optimization
• Significant experience designing MCP integrations and knowledge systems at scale, including tool server architecture, embedding pipelines, and context optimization
• Track record of setting technical strategy that spans multiple teams and multi-year time horizons
• Experience partnering with senior leadership (Directors, VPs) to align technical direction with business objectives
• Demonstrated ability to make high-stakes technical decisions under extreme ambiguity
• Strong mentorship track record, particularly in developing senior engineers toward staff-level impact
• Demonstrated curiosity and continuous learning in the rapidly evolving AI/LLM space
  

Bonus

• Strong proficiency in Python and experience with Django or similar backend frameworks
• Full-stack capabilities with React and TypeScript
• Experience building and scaling internal AI/ML platforms or developer experience infrastructure
• Familiarity with LLM orchestration frameworks (LangChain, LangGraph, or equivalent)
• Deep expertise in advanced agent architectures: multi-agent coordination, autonomous planning, or complex tool    ecosystems
• Experience with AI evaluation, observability, and production monitoring at enterprise scale
• Published technica