confluent - Director, Engineering – Applied AI

• Own and deliver the Applied AI platform layer — including LLM gateway and model routing, agent orchestration framework, HITL infrastructure, agent lifecycle management, identity and access controls, runtime guardrails, audit logging, cost governance, and kill-switch infrastructure • Build and lead a high-performing Applied AI engineering team, establishing the engineering culture, standards, and delivery practices • Design and ship a portfolio of agent builder capabilities spanning no-code tooling through high-complexity programmatic frameworks, enabling both technical and non-technical teams to deploy agents on a shared, governed platform • Partner with ACE (AI Center of Enablement) functional leads and business stakeholders across Sales, Support, Product, Marketing, Finance, and Legal to translate workflow acceleration goals into platform requirements, ensuring infrastructure keeps pace with deployment demand • Establish and own the risk and reliability posture for all agent workloads — including runtime security enforcement, escalation thresholds, override monitoring, and compliance controls • 5+ years of engineering leadership experience, with a track record of building and shipping production-grade platform, developer tooling, or internal application systems • Strong technical depth in platform design and distributed systems, with the ability to set architectural direction and make principled decisions around shared infrastructure vs. point solutions • Experience building developer-facing platforms or internal applications that serve audiences of varying technical sophistication — from engineers to non-technical business users • Experience leading or operating within an AI-native engineering team that actively uses AI-assisted development practices and tooling to design, build, and ship software • Proven ability to partner cross-functionally and translate ambiguous business problems into clear platform requirements and engineering roadmaps • WHAT GIVES YOU AN EDGE: • Experience building internal AI platforms or developer tooling at an enterprise SaaS, hyperscaler, or AI-native company • Familiarity with agent orchestration frameworks (e.g., LangGraph, Semantic Kernel, CrewAI) and LLM gateway or routing patterns • Background working in environments with explicit security, compliance, or audit requirements — financial services, healthcare tech, or regulated enterprise SaaS • Experience designing no-code or low-code builder surfaces alongside programmatic APIs on a shared underlying platform • READY TO BUILD WHAT'S NEXT? LET’S GET IN MOTION. • COME AS YOU ARE • Belonging isn’t a perk here. It’s the baseline. We work across time zones and backgrounds, knowing the best ideas come from different perspectives. And we make space for everyone to lead, grow, and challenge what’s possible.