Sr. Software Engineer, Applied AI Systems

Dialpad · Denver, USsenior

En corto

▸Construyes sistemas backend escalables para IA autónoma en tiempo real.
▸Trabajas con científicos de aplicaciones para llevar modelos de IA a producción.
▸Destacado: Eres clave para integrar, evaluar y monitorear DialpadGPT en productos reales.

Proficiency in English is required for collaboration across global teams.

En ~1 minuto te damos: quién te entrevista, las preguntas probables con respuestas desde tu CV, y tu CV adaptado a esta vacante. Gratis, sin tarjeta.

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¿Qué piden?

✓Experiencia en diseño de sistemas backend escalables.
✓Conocimiento en integración de modelos de IA en producción.
✓Habilidades en colaboración con científicos de aplicaciones.
✓Experiencia con sistemas distribuidos y microservicios.
✓Compromiso con la calidad y la operabilidad de sistemas de IA.
✓Capacidad para trabajar en entornos ágiles y con alta incertidumbre.

¿No cumplís todo? Es lo normal — tu dossier gratis te dice qué gaps tenés y cómo cubrirlos en la entrevista.

PythonGoJavagRPCKubernetesDockerPostgreSQLRedisAWSMLflow

¿A quién escribirle en Dialpad?

Tu dossier gratis identifica a las personas que te entrevistarían — con su background, qué valoran y cómo escribirles para destacar antes de aplicar.

About Dialpad Dialpad is the AI platform for customer experience, built to resolve customer problems in real time across voice and digital. Our AI agents learn from your best human agents and improve with every interaction, helping organizations understand their customers, deliver better experiences, increase operational efficiencies, and build a lasting competitive advantage. Unlike legacy systems built to route and answer, or standalone agentic bot vendors built to deflect, Dialpad was built to resolve. Our AI agents and human agents operate on a single platform with shared context, allowing Agentic AI to resolve issues, advance deals, and eliminate busywork through automation while seamlessly handing conversations to humans when needed, with full context preserved. Market-leading brands, including Randstad, Motorola Solutions, Netflix, the San Diego Padres, the Colorado Rockies Baseball Club, and Cal Athletics, trust Dialpad. Dialpad is backed by Andreessen Horowitz, GV, ICONIQ Capital, and T-Mobile. Being a Dialer At Dialpad, AI isn’t just a feature; it’s how our teams do their best work every day. We put powerful AI tools in every employee’s hands so they can move faster, think bigger, and achieve more. We believe every conversation matters. And we’ve built the platform that turns those conversations into insight and action, for our customers and ourselves. We look for people who are intensely curious and hold themselves to a high bar. Our ambition is significant, and achieving it requires a team that operates at the highest level. We seek individuals who embody our core traits: Scrappy, Curious, Optimistic, Persistent, and Empathetic . Your role Dialpad is building AI that helps businesses communicate, resolve customer needs, and automate work in real time. Our Applied AI team develops models, agentic capabilities, and evaluation methods that power these experiences. As a Sr. Software Engineer, Applied AI Systems, you will build the software systems that power Dialpad’s next-generation agentic AI. You will work closely with Applied Scientists and partner with engineering teams to turn advanced AI capabilities into reliable, scalable customer-facing experiences. This is a hands-on role for an engineer who enjoys building agentic systems at the intersection of AI, backend services, and product delivery. You will help shape how DialpadGPT models are integrated, evaluated, monitored, and deployed in next-generation AI products, including real-time conversational experiences. What you’ll do • Design and build scalable backend services and distributed systems for agentic AI applications. • Partner with Applied Scientists to bring models, evaluation methods, and agentic capabilities from prototype to production. • Build software that connects models, tools, data, and evaluation

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