Senior Backend Engineer

About the role

Title: Sr. Backend Engineer
Function: Engineering
Reporting: VP of AI Product
Location: San Fransico, CA (Hybrid)

Responsibilities

• A multi-tenant execution sandbox for agents with strict, provable data isolation.
• The durable execution backbone on Temporal, so long-running agent runs survive failures, restarts, and retries.
• The agent harness and SDKs: tool-calling, context, model orchestration, and the eval and guardrail loops that keep behavior safe.
• MCP tool exposure and external runtime interop.
• Observability and audit infrastructure for agent execution.
• The failure model: error handling, resource limits, and graceful degradation.

Qualifications

• Built an agentic framework or runtime end-to-up, not just used one.
• You have designed the agent loop yourself: tool-calling, context management, multi-agent orchestration, eval and guardrail loops, and the failure modes specific to agents.
• You can speak to the trade-offs you made and what you would do differently.
• 6+ years building backend systems or distributed infrastructure at scale.
• Built SDKs or platforms that other engineers build on top of.
• Prediction use of AI-assisted dev tools (Claude Code, Codex, Gemini CLI, or similar) across the full lifecycle: spec, build, review, and deploy validation.
• Multi-tenant design with hard tenant isolation, ideally in a regulated space (financial services, healthcare).
• Async and concurrent execution patterns (goroutines, async/await, thread pools).
• Secure API design with authn/authz at the service boundary.
• Observability and instrumentation: logging, tracing, audit trails.

Preferred Skills and Qualifications

• Workflow orchestration (Temporal, Airflow, Prefect), especially agentic workflows in production.
• Managed agent runtimes (Claude Managed Agents, Bedrock Agents, Google Agent Builder, Azure AI Services).
• Runtime isolation and sandboxing.
• Deep familiarity with agent dev kits (Google ADK, Claude Agent SDK, OpenAI SDK, LangChain, CrewAI, AutoGen) at the level of their internals, not just their APIs.
• MCP or similar tool and extension systems.
• gRPC or modern RPC.
• Multi-provider key management; secrets and credential rotation.
• Event-driven architecture (streaming, queues, event sourcing; Kafka or similar).
• Knowledge graphs for grounding agents (Neo4j, or Obsidian-style linked stores).
• Audit and compliance in regulated industries (PCI-DSS, SOC 2).
• Enterprise communication or messaging platforms.

Skills and Qualifications

• Built an agentic framework or runtime end-to-up, not just used one.
• You have designed the agent loop yourself: tool-calling, context management, multi-agent orchestration, eval and guardrail loops, and the failure modes specific to agents.
• You can speak to the trade-offs you made and what you would do differently.
• 6+ years building backend systems or distributed infrastructure at scale.
• Built SDKs or platforms that other engineers build on top of.
• Prediction use of AI-assisted dev tools (Claude Code, Codex, Gemini CLI, or similar) across the full lifecycle: spec, build, review, and deploy validation.
• Multi-tenant design with hard tenant isolation, ideally in a regulated space (financial services, healthcare).
• Async and concurrent execution patterns (goroutines, async/await, thread pools).
• Secure API design with authn/authz at the service boundary.
• Observability and instrumentation: logging, tracing, audit trails.