Member of Technical Staff

Conduit

San Francisco (CA)

On-site

USD 130,000 - 220,000

Full time

14 days+

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Benefits offered by this job

Health insurance
401(k) match
Equity

Job summary

Conduit, an AI agent platform for hospitality, is seeking a Member of Technical Staff. There is no hierarchy and you can work anywhere in the stack, owning the modules you touch and shaping the platform with real-world impact.

You will direct a fleet of agents, design end-to-end pipelines, integrate tools and APIs, and ensure observable, reliable performance across guest-facing and internal workflows. Join a small, empowered team delivering fast, concrete results.

Qualifications

  • Shipped production systems used by real users.
  • Comfortable across the stack.
  • Strong focus on retrieval quality and evaluation.

Responsibilities

  • Build end-to-end AI agent platforms and tools.
  • Design reliable knowledge retrieval and tool orchestration.
  • Implement observability and evaluation for safety and ROI.

Job description

About Conduit

Conduit is an AI agent platform purpose-built for hospitality. Hotels, vacation rentals, and resorts deploy our agents across guest-facing communication and internal operations, running millions of workflows a day.

Hospitality is 10% of global GDP and it turns on customer experience. Resolving a guest request immediately is most of that experience, and resolving one means moving across several tools and between several people. That coordination is the work, and it is what our agents do.

Role: Member of Technical Staff

There is no hierarchy on the engineering team and everyone can work anywhere in the stack. People end up specializing in the product lines they gravitate toward, but that happens on its own rather than by assignment. We want the engineering org as flat as we can keep it.

Why this role is different
  • Free rein with AI agents, and full ownership of what comes out. Nobody tells you which tools to reach for or how much of the work to hand off. Where to use an agent and where to do it yourself is your call, and how well you make that call is what we evaluate you on.
  • You will touch most of the stack and end up owning parts of it. You work across the codebase instead of in one lane. The modules you go deep on become yours, and the team depends on you for them.
  • The design decisions are yours to make. You choose the approaches, and the ones that hold up stay in the platform for decades. That is real weight to carry and it is most of why the role is interesting.
  • You are directing a fleet of agents. You sketch the work, design it carefully, and the agents execute against that design in parallel. You get a lot of output for each unit of work you put in, and getting good at running that is a skill that follows you everywhere else.
What the work looks like
  • Response generation pipeline. The router, orchestrator, and synthesizer that classify intent, assemble context, select tools, generate a response, and decide whether to send it or elevate.
  • Knowledge retrieval. Models ground their answers in whatever context they are given, so reliability comes down to whether that context is correct, complete, and current. Customer data is usually none of those. You build the retrieval, ranking, and validation that makes the output trustworthy anyway: a hierarchical knowledge base with scope-based queries, contradictory docs, stale articles, and the edge cases that live in one rep’s head.
  • Tool orchestration. The agents modify reservations, dispatch maintenance, send confirmations, and close the loop. You design the tool-use and function-calling layer that runs multi-step workflows end to end, including what happens when a third-party API goes down mid-conversation.
  • Evaluation and testing. The eval framework that measures quality against real conversations and catches regressions before customers see them.
  • Observability. The trace that shows what the agent retrieved, what it considered, what it ignored, where confidence dropped, and why it chose what it did. That trace is what lets a CX team trust the system and improve it.
  • Controls for people who are not engineers. The people running these agents day to day are support leads. You make the agent’s behavior legible, testable, and adjustable by someone who has never written code.
  • Voice. Real-time conversations with transcription and the same tool use as text, under tighter latency.
  • Speed and cost. Model routing, caching, prompt optimization.
  • Infrastructure, data pipelines, integrations, and API work. The systems underneath all of the above.
Who you are
  • You have shipped production systems that real users depend on.
  • You are comfortable anywhere in the stack and pick up whatever the problem needs.
  • You think about retrieval as seriously as generation.
  • You are pragmatic about models. Sometimes the right answer is a frontier model, sometimes a small fine‑tuned one, sometimes a regex.
  • You care about evaluation. You do not ship a prompt change without knowing what it does across a thousand real conversations.
  • You want a small team where the thing you push changes the product that day.
Compensation and Benefits
  • $130-220K base
  • 0.20%-1.20% equity
  • Comprehensive health insurance and 401k match
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