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.

• 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

• 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

• 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
• Contributions to AI/ML open-source projects or technical publications