Senior 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 enterprise performance management 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.   Join a talented, fast-growing team committed to solving some of the most complex and impactful problems in sales performance management.   About the Role CaptivateIQ is building AI capabilities that will transform how enterprises manage sales performance. We're looking for a **Senior Software Engineer** to join our Agentic SDK team, an internal developer platform that enables product teams across the company to build AI-powered features.

This is a technical leadership role on a small, high-impact team. You'll own the technical roadmap for complex AI projects, making architectural decisions that shape how AI gets built across the organization. Working across the full stack, from React/TypeScript frontends to Python backends and LLM orchestration systems, you'll define patterns and best practices that other engineers will follow.

You'll lead by example: shipping high-quality code, mentoring teammates, and making challenging technical decisions when the path forward isn't clear. As one of five engineers pioneering AI at CaptivateIQ, you'll have direct influence on team-level outcomes and accountability for alignment to our technical strategy.

This is a greenfield opportunity with outsized impact. You'll help establish the foundations of our AI platform while coaching P3 engineers and contributing to the engineering culture that will scale with the company.

 

Responsibilities

• Define and own the technical roadmap for complex AI platform initiatives, driving semi-annual and annual milestones
• Architect and implement production-grade LLM orchestration systems, including agent frameworks, tool calling, and multi-step reasoning workflows
• Design MCP integrations and knowledge management systems, including tool orchestration, embedding strategies, and context optimization
• Lead technical design for cross-functional AI features, making challenging decisions when trade-offs are unclear
• Establish coding standards, review practices, and architectural patterns for AI development across the Agentic SDK team
• Coach and mentor P3 engineers, helping them grow toward senior-level scope and autonomy
• Partner with product teams to translate ambiguous business needs into technical solutions, ensuring alignment to company strategy

Requirements

• 5+ years of professional software engineering experience with demonstrated progression into technical leadership
• Deep proficiency in Python with experience architecting production backend systems (Django strongly preferred)
• Strong frontend development skills with React and TypeScript, including experience with complex state management
• Significant hands-on experience with LLM APIs and building orchestration systems (agent workflows, tool calling, multi-step reasoning)
• Experience designing and implementing MCP integrations, including tool servers, embedding models, and context management strategies
• Track record of defining technical roadmaps and leading projects from conception through delivery
• Experience mentoring engineers and elevating team technical practices
• Strong ability to make decisions under ambiguity and communicate technical trade-offs to stakeholders
• Demonstrated curiosity and continuous learning in the rapidly evolving AI/LLM space

Bonus Points

• Experience building internal developer platforms, SDKs, or shared AI/ML infrastructure
• Familiarity with LLM orchestration frameworks (LangChain, LangGraph, or equivalent)
• Deep expertise in agent architectures: multi-agent systems, tool use, planning algorithms, or memory systems
• Experience with prompt optimization, evaluation frameworks, or LLM observability tools (LangSmith, Weights & Biases)
• Background in building AI features that shipped to enterprise customers
• Experience at a B2B SaaS company scaling from Series B through growth stage
• Familiarity with sales performance, commissions, or financial software domains