Principal Engineer - Agentic Data Plane

Responsibilities

• Track emerging research, frameworks, and industry developments in the agentic AI space, and translate the most relevant signals into concrete engineering proposals and product bets
• Identify, prototype, and deliver high-leverage emerging capabilities for ADP, in partnership with the broader team
• Define architectural patterns for new ADP capabilities, ensuring they integrate cleanly with the existing runtime, policy, and observability layers
• Engage directly with strategic customers and the field to stress-test new capabilities against real enterprise deployment scenarios
• Serve as a technical ambassador for ADP externally, publishing research, writing engineering blog posts, and speaking at conferences to establish Redpanda's credibility at the frontier of agentic infrastructure
• Participate in on-call and help drive down operational toil, improving system observability and self-healing capabilities over time

Requirements

• 10+ years of software engineering experience, with a demonstrated track record of leading the design and delivery of complex, large-scale distributed systems
• Experience building or contributing to emerging areas of agentic AI infrastructure, e.g. eval frameworks, orchestration layers, context management, AI gateways, or similar
• Fluency with AI-assisted development at the level of agentic orchestration, i.e. composing multi-agent coding workflows with subagents to dramatically accelerate research and prototyping
• Deep expertise in at least one systems language (Go preferred) and comfort working across the stack
• Understanding of streaming data systems, messaging infrastructure, or data plane/control plane architectures, experience with Apache Kafka or Redpanda is a plus
• Experience designing and operating systems that enforce access control, policy, and auditability at scale
• Self-directed, strong written communicator, comfortable collaborating asynchronously in GitHub, Slack, and Google Docs
• Excellent interpersonal and communication skills. Able to lead without authority across engineering teams and engage credibly with technical customers and external audiences

Nice to Have

• Familiarity with AI safety, alignment, or responsible AI research as it applies to autonomous systems in enterprise environments
• Experience with protocol buffers, protoreflect and codegen
• Background in security, identity, or data governance systems relevant to enterprise environments
• Experience running Kafka/Redpanda and/or Postgres at scale
• Experience with Kubernetes and cloud-native infrastructure across AWS, GCP, or Azure
• Prior experience in an early-stage or growth-stage startup, especially in a category-defining product area

Compensation

U.S. base salary range for this role is $245,000 - $290,000. Salary ranges are determined by role, level, and location.