Staff Software Engineer - AI Platform

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.

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