Member Technical Staff - Applied AI Engineer
Build and operate customer-facing agentic systems that automate support workflows, diagnose issues, and safely execute bounded actions. The role requires 2–4 years of software engineering experience, production AI systems experience, and strong backend or integration debugging skills.
About the job
Responsibilities
- Build agentic workflows for support intake, classification, context gathering, reproduction, diagnosis, response drafting, remediation, verification, and follow-up.
- Develop tool-using agents that inspect runs, logs, authentication state, configuration, and provider behavior, and execute bounded recovery actions safely.
- Create evaluation suites for diagnostic correctness, resolution quality, safe escalation, customer communication, and end-to-end task completion.
- Build human-in-the-loop systems with explicit ownership, uncertainty, approvals, handoffs, and failure states.
- Develop observability, memory, and feedback loops that improve agents from real support cases.
- Ship product improvements that eliminate recurring classes of customer issues.
- Own customer issues end to end by reproducing, isolating, mitigating, shipping, communicating, and verifying resolutions.
- Collaborate with customers and Support, FDE, Product, and Engineering teams to turn recurring work into software.
- Move prototypes into reliable production workflows with traces, evaluations, guardrails, and human fallbacks.
Requirements
- 2–4 years of professional software engineering experience.
- Production experience with language models, tool calling, retrieval, structured outputs, multi-step workflows, or agent memory.
- Experience building and operating production backend, platform, or integration systems.
- Ability to debug SDKs, HTTP, OAuth, webhooks, queues, data stores, logs, and third-party APIs.
- Ability to turn ambiguous failures into minimal reproductions, root causes, and durable fixes.
- Strong communication with technical users and comfort working directly with customers.
- Ability to model support functions using states, tools, permissions, handoffs, verification steps, and escalation rules.
- Judgment about what to automate versus keep human-controlled while maintaining trust.
Nice-to-haves
- Production TypeScript or Python experience.
- Experience building AI agents, copilots, workflow automation, or evaluation infrastructure.
- Experience with developer platforms, API products, support engineering, SRE, or incident response.
- Familiarity with OAuth 2.0, webhooks, rate limits, PostgreSQL, queues, and cloud observability.
- Experience with Plain, Zendesk, Intercom, or Salesforce.
- Public technical writing or open-source contributions.
Skills
Python, TypeScript, LLMs, Tool Calling, Retrieval, Structured Outputs, Agent Workflows, Agent Memory, Backend Engineering, Http, Oauth 2.0, Webhooks, Postgres, Queues, Cloud Observability
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