Director, Engineering - Applied AI

Location:Remote, United StatesEmployment Type:FullTimeLocation Type:RemoteDepartmentBusiness TechnologyCompensation:$322.5K - $387K - Offers EquityAt Confluent, we are committed to providing competitive pay that is in line with industry standards. We analyze and carefully consider several factors when determining compensation, including work history, education, professional experience, and location. The actual pay may vary depending on your skills, qualifications, experience, and work location.OverviewWe're not just building better tech. We're rewriting how data moves and what the world can do with it. With Confluent, data doesn't sit still. Our platform puts information in motion, streaming in near real-time so companies can react faster, build smarter, and deliver experiences as dynamic as the world around them.It takes a certain kind of person to join this team. Those who ask hard questions, give honest feedback, and show up for each other. No egos, no solo acts. Just smart, curious humans pushing toward something bigger, together.One Confluent. One Team. One Data Streaming Platform.About the Role:Most companies are still figuring out where AI fits. At Confluent, we're moving past that question - and building the infrastructure that makes AI a trusted, supervised part of how work actually gets done. As Director of Applied AI Engineering, you will own that foundation: the agent orchestration platform, LLM gateway, runtime guardrails, audit logging, and the full lifecycle infrastructure that turns AI experimentation into durable business execution. This is a rare opportunity to shape something from the ground up - hiring the team, setting the architecture, and staying hands-on as a technical contributor to the platform itself. You won't just lead the work; you'll be in it. You will work closely with leaders across Sales, Support, Product, Marketing, Finance, and Legal, ensuring the platform you build accelerates the workflows that most directly influence revenue, customer trust, and monetization speed - with reliability, security, and human oversight built in from the start.What You Will Do: 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 What You Will Bring: 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 AreBelonging 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.We're proud to be an equal opportunity workplace. Employment decisions are based on job-related criteria, without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other classification protected by law.

Created: 2026-03-14