Agent Deployment Engineer - German Speaking

Decagon·Londonmid

In short

→Ingeniero de despliegue de agentes de IA que implementa y escala agentes para clientes empresariales.
→Trabajas con clientes técnicos y equipos internos para diseñar, construir y validar agentes de IA en múltiples canales.
→Destaca por ser un rol técnico y de entrega con enfoque en IA generativa y despliegue en entorno empresarial.

Fluent English required; German spoken (required)

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What they ask for

✓Experiencia en desarrollo de software o ingeniería de sistemas
✓Conocimiento práctico de IA generativa y LLMs
✓Capacidad para trabajar con clientes técnicos a alto nivel
✓Habilidades de resolución de problemas y análisis de errores
✓Inglés avanzado (requisito clave)
✓Alemán hablado (requisito esencial)

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LLMsConversational AIAPIsData PipelinesCRMsTicketing SystemsModel EvaluationRoot-Cause AnalysisGuardrailsAgent Architecture

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About Decagon Decagon is the leading conversational AI platform empowering every brand to deliver concierge customer experiences. Our technology enables industry-defining enterprises like Avis Budget Group, Block’s Cash App and Square, Chime, Oura Health, and Hunter Douglas to deploy AI agents that power personalized, deeply satisfying interactions across voice, chat, email, SMS, and every other channel. We’re building a future where customer experiences are being redefined from support tickets and hold music to faster resolutions, richer conversations, and deeper relationships. We’re proud to be backed by world-class investors who share that vision, including a16z, Accel, Bain Capital Ventures, Coatue, and Index Ventures, along with many others. We’re an in-office company, driven by a shared commitment to excellence and velocity. Our values — Just Get It Done, Invent What Customers Want, Winner’s Mindset, and The Polymath Principle — shape how we work and grow as a team. About the Team Over the past few years, development of LLMs has evolved at a rapid pace. It’s not enough for our customers to just “set it and forget it” when it comes to AI software. Truly successful AI Agents require hands-on execution, rigorous iteration, and deep technical delivery to reach enterprise-grade performance. We’re creating an Agent Deployment Engineering Org : a specialized technical delivery team responsible for end-to-end execution of AI agent builds. Agent Deployment Engineers own the hands-on work required to deliver best-in-class agents—writing and configuring key components, validating integrations, and ensuring agents perform reliably at scale. This team brings greater specialization and focus to build quality. Agent Deployment Engineers are technical and customer-facing: you’ll interface with senior technical stakeholders on the customer side while also going deep on agent configuration and build execution. About the Role As an Agent Deployment Engineer, you will be responsible for end-to-end execution of AI agent builds for strategic customers. This is a highly technical delivery role where you will own the implementation work required to launch and scale enterprise-quality agents—partnering with customers and internal teams to define success, translate requirements into build plans, and deliver agents that meaningfully impact the customer’s business. You’ll work closely with Agent PMs, Agent Success, Engineering, and GTM teams to create tight feedback loops: executing builds, surfacing gaps, and influencing the evolution of Decagon’s agent-building platform based on real customer needs. This role is ideal for someone who thrives in fast-moving environments, enjoys shipping customer-facing technical work, and can balance hands-on execution with structured thinking. In this role, you will Own end-to-end architecture and execution of AI agent builds for enterprise customers, from systems design and initial scoping through implementation, evaluation, and production deployment. Design and engineer the core agentic logic governing agent behavior, applying engineering principles to optimize quality, reliability, and correctness across non-deterministic model outputs. Engineer and validate layered guardrails and supervisory controls to ensure safe, compliant, and predictable agent performance across real-world scenarios. , data pipelines, CRMs, ticketing systems), including building the tools, APIs, and workflows needed for reliable deployments at scale. Interface with senior technical stakeholders at customers to define success criteria and system requirements, and drive technical delivery against timelines. Diagnose, debug, and resolve both probabilistic and technical failures through root-cause analysis of execution traces, error logs, and model behavior.

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