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Requirements and qualifications

Engineering

What you will get

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Polyai

Forward Deployed Engineer, Agentic AI

📍 Germany, 💼 –+ years🏠 On-site◷ Full Time

About the role

<div class="content-intro"><p><sup><span style="font-family: helvetica, arial, sans-serif;"><span><a href="https://poly.ai?utm_source=prnewswire&amp;utm_medium=pressrelease&amp;utm_campaign=boilerplate&amp;utm_content=pressrelease" target="_blank">PolyAI</a></span> is the Agentic Dialog Platform for building the conversational enterprise, used to build, run, govern, and improve dialog agents at scale. Powered by Raven, a proprietary dialog model trained on more than a billion enterprise conversations, PolyAI agents are built for complexity, open at every layer, and sovereign by design. PolyAI serves hundreds of enterprises across 75 languages and 25 countries, including Metro Bank, Marriott, PG&amp;E, and UniCredit.</span></sup></p></div><h3><sup><span style="font-family: helvetica, arial, sans-serif;">The role</span></sup></h3>
<p><sup><span style="font-family: helvetica, arial, sans-serif;">Most AI agents are demos. Ours answer the phone for some of the biggest brands in the world: more than 100 million calls a year, across 2,000+ live deployments. Someone is on the line trying to move a booking, report a fault or pay a bill, and the agent either works or it doesn't.</span></sup></p>
<p><sup><span style="font-family: helvetica, arial, sans-serif;">We looking for a Forward Deployment Engineer who has built and shipped LLM agents in production, including tool use and evals. Forward Deployed Engineers are the people who make it work. </span></sup><sup><span style="font-family: helvetica, arial, sans-serif;">You own a customer's agents from the first scoping call through to production and beyond. You design how the agent behaves, write the code that connects it to the customer's systems, put it on their phone lines, measure it and keep making it better.</span></sup></p>
<p><sup><span style="font-family: helvetica, arial, sans-serif;">This is not sales engineering and it is not support. You ship code that runs in production, and you own what happens after it ships.</span></sup></p>
<p><sup><span style="font-family: helvetica, arial, sans-serif;">We want someone who already builds agents because they can't help it, and who wants to do it at the hard end: real-time voice, messy enterprise systems, and callers who notice every mistake.</span></sup></p>
<h3><sup><span style="font-family: helvetica, arial, sans-serif;">What you'll do</span></sup></h3>
<ul>
<li style="font-family: helvetica, arial, sans-serif; font-size: 12pt;"><sup><span style="font-family: helvetica, arial, sans-serif;">Own agents in production, end to end. Scope with the customer; design the conversation, the tools and the guardrails; build in Agent Studio and our ADK; launch; and stay accountable for how it performs.</span></sup></li>
<li style="font-family: helvetica, arial, sans-serif; font-size: 12pt;"><sup><span style="font-family: helvetica, arial, sans-serif;">You have built and shipped LLM agents in production, including tool use and evals&nbsp;</span></sup></li>
<li style="font-family: helvetica, arial, sans-serif; font-size: 12pt;"><sup><span style="font-family: helvetica, arial, sans-serif;">Connect agents to the real world. Integrate CRMs, booking engines, payment flows and twenty-year-old APIs in Python. Work across SIP, telephony and contact-centre platforms. Make tool calls fast and reliable in the middle of a live conversation.</span></sup></li>
<li style="font-family: helvetica, arial, sans-serif; font-size: 12pt;"><sup><span style="font-family: helvetica, arial, sans-serif;">Debug live calls. When a call goes wrong, work out whether it was the speech recognition, the model, the prompt, an integration or the phone line, and fix the right thing.</span></sup></li>
<li style="font-family: helvetica, arial, sans-serif; font-size: 12pt;"><sup><span style="font-family: helvetica, arial, sans-serif;">Run agents like a scientist. Build eval sets from real calls, run A/B tests and let data decide what ships. Containment, resolution and caller experience are your numbers.</span></sup></li>
<li style="font-family: helvetica, arial, sans-serif; font-size: 12pt;"><sup><span style="font-family: helvetica, arial, sans-serif;">Close the gap to the platform. When you solve something for one customer, turn it into a reusable tool, template or product change so the next deployment is faster. Work directly with product, research and platform engineering, including the team training Raven, our own LLM built for customer service.</span></sup></li>
<li style="font-family: helvetica, arial, sans-serif; font-size: 12pt;"><sup><span style="font-family: helvetica, arial, sans-serif;">Be the technical lead the customer trusts. Run sessions with their engineering, operations and executive teams. Explain trade-offs plainly. Say no when no is the right answer.</span></sup></li>
<li style="font-family: helvetica, arial, sans-serif; font-size: 12pt;"><sup><span style="font-family: helvetica, arial, sans-serif;">Work AI-native. You use coding agents and LLM tooling every day, and you help the people around you do the same.</span></sup></li>
</ul>
<h3><sup><span style="font-family: helvetica, arial, sans-serif;">You'll fit if</span></sup></h3>
<ul>
<li style="font-family: helvetica, arial, sans-serif; font-size: 12pt;"><sup><span style="font-family: helvetica, arial, sans-serif;">You have shipped LLM-powered agents or conversational systems to real users, and you can show us one.</span></sup></li>
<li style="font-family: helvetica, arial, sans-serif; font-size: 12pt;"><sup><span style="font-family: helvetica, arial, sans-serif;">You write strong Python and are at home in production code, APIs and integrations, including codebases you didn't write.</span></sup></li>
<li style="font-family: helvetica, arial, sans-serif; font-size: 12pt;"><sup><span style="font-family: helvetica, arial, sans-serif;">You have several years in a technical, customer-facing engineering role: forward deployed, solutions engineering that ships real code, consulting engineering, or a startup where you were the engineer customers called.</span></sup></li>
<li style="font-family: helvetica, arial, sans-serif; font-size: 12pt;"><sup><span style="font-family: helvetica, arial, sans-serif;">You own outcomes, not tickets. You have been the person on call when it broke, and you liked it.</span></sup></li>
<li style="font-family: helvetica, arial, sans-serif; font-size: 12pt;"><sup><span style="font-family: helvetica, arial, sans-serif;">You can explain a latency budget to an engineer and a containment trade-off to a COO in the same afternoon.</span></sup></li>
</ul>
<h3><sup><span style="font-family: helvetica, arial, sans-serif;">Even better</span></sup></h3>
<ul>
<li style="font-family: helvetica, arial, sans-serif; font-size: 12pt;"><sup><span style="font-family: helvetica, arial, sans-serif;">Voice and telephony: SIP, IVR, CCaaS platforms, real-time audio.</span></sup></li>
<li style="font-family: helvetica, arial, sans-serif; font-size: 12pt;"><sup><span style="font-family: helvetica, arial, sans-serif;">Evals and experimentation, or an ML background: you have built a test set or run an online experiment.</span></sup></li>
<li style="font-family: helvetica, arial, sans-serif; font-size: 12pt;"><sup><span style="font-family: helvetica, arial, sans-serif;">Regulated industries such as healthcare, utilities or financial services.</span></sup></li>
<li style="font-family: helvetica, arial, sans-serif; font-size: 12pt;"><sup><span style="font-family: helvetica, arial, sans-serif;">Go or C++, or high-throughput real-time systems.</span></sup></li>
</ul>
<h3><sup><span style="font-family: helvetica, arial, sans-serif;">Why PolyAI</span></sup></h3>
<ul>
<li style="font-family: helvetica, arial, sans-serif; font-size: 12pt;"><sup><span style="font-family: helvetica, arial, sans-serif;">Voice is the hard channel, and it's all we do. Real-time, interruptible, noisy, on phone lines built decades ago. Doing it well at enterprise scale is a moat, and you will learn things here you can't learn anywhere else.</span></sup></li>
<li style="font-family: helvetica, arial, sans-serif; font-size: 12pt;"><sup><span style="font-family: helvetica, arial, sans-serif;">We own the stack that matters. Raven is our own LLM, trained for customer service inside the agent harness. When the model is the problem, the people who can fix it sit down the corridor.</span></sup></li>
<li style="font-family: helvetica, arial, sans-serif; font-size: 12pt;"><sup><span style="font-family: helvetica, arial, sans-serif;">Real production, real stakes. Your agents go live for brands people have heard of, and you will see the impact in their numbers within weeks.</span></sup></li>
<li style="font-family: helvetica, arial, sans-serif; font-size: 12pt;"><sup><span style="font-family: helvetica, arial, sans-serif;">Ownership early. Small teams, each engineer owning accounts. The best ideas from the field become the product.</span></sup></li>
<li style="font-family: helvetica, arial, sans-serif; font-size: 12pt;"><sup><span style="font-family: helvetica, arial, sans-serif;">London HQ. Founded by conversational-AI researchers from Cambridge, with teams in London and North America.</span></sup></li>
</ul>
<p><sup><span style="font-family: helvetica, arial, sans-serif;">We offer competitive compensation based on experience, expertise, and the level of responsibility. This role also includes equity, giving you the opportunity to share in the long-term success

Requirements

  • Engineering

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