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# Forward Deployment Engineer

- **Company:** Polyai
- **Location:** London, United Kingdom (Remote available)
- **Contract:** Temporary contract
- **Skills:** A/B Testing, Application Programming Interfaces (APIs), Artificial Intelligence, C++ (Programming Language), Software Debugging, Python (Programming Language), Systems Integration, Speech Recognition, Real Time Systems, Large Language Models, Production Code
- **Published:** November 11, 2026
- **Apply:** https://startup.jobs/forward-deployed-engineer-agentic-ai-polyai-company-10738826

## About the Role

* ^You have shipped LLM-powered agents or conversational systems to real users, and you can show us one.
 * ^You write strong Python and are at home in production code, APIs and integrations, including codebases you didn't write.
 * ^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.
 * ^You own outcomes, not tickets. You have been the person on call when it broke, and you liked it.
 * ^You can explain a latency budget to an engineer and a containment trade-off to a COO in the same afternoon.

## Description

^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., * ^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.

 * ^You have built and shipped LLM agents in production, including tool use and evals
 * ^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.
 * ^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.
 * ^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.
 * ^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.
 * ^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.
 * ^Work AI-native. You use coding agents and LLM tooling every day, and you help the people around you do the same.