We are looking for a product-minded AI engineer to turn what our customers are trying to decide into agents they actually rely on. AskWaive, our in-product assistant, is already live; the work now is quality, coverage, and an experience that wows.
This is not a role for a prompt author or a demo builder. We want an owner: someone who takes a customer need—already expressed through our serving layers and semantic layer—and turns it into an endpoint, a tool, and an experience that makes the customer measurably better at their job. Agent engineering, deployment, and testing are all part of delivery, not a handoff.
Our core data platform is owned by the team that built it. You'll build on top of it—and where data or infrastructure is holding an agent back, you'll have the standing to propose the change and drive it.
What You'll Do
From Customer Need to Product Superpower
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Own the Outcome: Start from the customer, and stay with it until the agent is answering their needs better
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Build Agents and Tools: Build production agents and the tools they call—retrieval, multi-step workflows, action-taking—on Amazon Bedrock, with Bedrock AgentCore as our runtime and tools exposed over MCP (Model Context Protocol).
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Turn Serving Layers Into Capability: Our semantic layer and service APIs are where customer needs are already expressed. Your job is turning them into endpoints and tools an agent can wield well—and knowing which metrics and entities it should reach at all.
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Shape the Experience, Not Just the Endpoint: How an answer arrives—its speed, its confidence, its explanation, the next step it offers—is the product. A technically correct response a customer ignores is a failure.
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Measure Groundedness: Build the eval harness—labeled test sets, groundedness and hallucination rates you can put a number on, and CI gates that stop a regression before it ships.
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Measure What Customers Got: Adoption, feedback, intent—then report realized impact back to Product and the business in numbers that hold up.
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Diagnose and Iterate: Instrument the tracing that shows why an answer was wrong, turn each failure mode into a specific fix, and ship again. This loop is the job, not a phase of it.
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Ship and Operate: Own the serving path—MCP endpoints, latency, cost per response, caching, and runtime guardrails. Deployment and testing are part of the job, not a handoff.
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Embed and Influence: Partner with Product Managers and engineers on which decisions an agent should support—and which it shouldn't. Where data or infrastructure limits what an agent can do, drive the change alongside the team that owns the platform.
Prove It and Make It Felt
Deliver
Who You Are
The Owner: You measure your work by whether customers made better decisions with the agent's help, not by whether it shipped.
The Agent Builder: You've taken an agent past the demo. You know the hard part is everything after it works once—coverage, grounding, cost, and the failure modes you only see at scale. You fix problems without waiting for a ticket.
The Experience Obsessive: You care how an answer lands, not just whether it was right. Trustworthy, fast, and legible beats clever.
We know that great talent comes from many backgrounds. If you are a builder who cares about the "why" behind the code, we want to hear from you!
HOW WE WORK
We build with coding agents. You set direction
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