Perplexity is looking for a Software Engineer to build the core infrastructure that powers agentic products across Perplexity including Search, Deep Research, and the Comet browser. You will design and evolve the runtime, orchestration, evaluation and training systems that let agents plan, use tools, browse, and verify at scale.

Responsibilities

• Design and implement a highly reliable and scalable agent runtime: orchestration, shared state and memory, tool calling interfaces, and scheduling for cost, latency, and quality.

• Build secure sandboxed execution for agent actions and code. Optimize cold start, isolation, and observability.

• Ship unified interfaces for multiple model sizes and providers. Integrate with open tool ecosystems such as MCP style connectors for data and actions.

• Develop an evaluation platform for online and offline assessments, A/B tests, safety checks, and regression gates that improve agent reliability over time.

• Partner with Research, Inference, and Search to land new agent capabilities end to end, from prototype to production.

Qualifications

• 6+ years of industry experience building large scale systems or platforms.

• Experience building agent applications with tool calling, context engineering, or open connector integrations.

• Strong coding skills in one or more of: Python, Java, Go. Comfortable with service design, APIs, and data models for high throughput systems.

• Working knowledge of containers, virtualization, and sandboxing. Familiar with metrics, tracing, on call, and incident practices.

• Bias to own problems across layers, collaborate in fast moving teams, and ship.

Nice to have

• Prior work on agent orchestration pipelines: task routing, planning, memory graphs, vector search, or browser automation.

• Experience with evaluations, preference optimization, or RL to improve agent reliability.

• Exposure to MCP or similar open protocols for tool and data connectivity.

• Security hardening for multi tenant workloads, snapshotting, or untrusted code execution.