Engineering Manager, AI Transformation

Dialpad · Buenos Aires, Argentina
full-time lead Posted 2 months ago
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About this role

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 As the Manager of AI Transformation Engineering, you will be the technical anchor for the AIT team. This is a lead-from-the-front role: you will set engineering standards, guide teammates through complex implementation challenges, establish evaluation practices, and own the technical quality of everything we ship. You will also drive upskilling across the team, coaching analysts and junior engineers, and helping them build the AI engineering depth needed to deliver reliable production systems. The role reports to the Senior Manager of AI Transformation, who handles stakeholder coordination and team operations. Your mandate is to own technical direction and execution. This role has the opportunity to be in Buenos Aires, Argentina. The successful candidate must be available during US overlapping hours (9 AM – 6 PM ART). What you'll do Set and enforce engineering standards across the team — architecture decisions, code quality, review practices, and evaluation frameworks to ensure systems actually work in production. Lead the design and implementation of AI-powered systems: agents, RAG pipelines, LLM-based automations, and workflow integrations, from specification through to production. Upskill analysts and junior engineers on AI engineering fundamentals: building reliable pipelines, evaluating LLM outputs, debugging failures, and moving from prototype to production. Own the team's technical tooling decisions — which models, orchestration frameworks, and infrastructure patterns to standardize on. Get into the code when the problem demands it; this is a hands-on role, not a coordination role. Translate ambiguous business problems into clear technical specifications that less senior teammates can execute against. Collaborate with Analytics, Sales, CX, Finance, and Operations teams to understand requirements and turn them into robust, reliable AI solutions. Define the team's AI evaluation practices so we ship systems we can trust — and continuously improve. Partner with the AI Transformation Manager to shape the technical roadmap and prioritize engineering investment. Proactively identify and address technical debt before it compounds into reliability problems. Skills you'll bring 8+ years of experience in software engineering, ML engineering, or AI systems development. Hands-on experience building and deploying LLM-powered systems in production: agents, RAG pipelines, or AI-driven automations. 1-3 years of management experience. Strong Python skills — you write, review, and debug production-grade code. Demonstrated experience leading or mentoring engineers or analysts, with a clear track record of raising the technical level of the people around you. Solid grasp of AI evaluation: how to measure whether a system does what it's supposed to do, and how to build feedback loops that drive continuous improvement. Experience with cloud platforms, preferably GCP. Comfort working across the full stack required to deploy AI tools: APIs, data pipelines, infrastructure, and monitoring. Strong written and verbal communication in English — able to articulate technical trade-offs clearly to non-technical stakeholders. Proven ability to collaborate with distributed and offshore teams and deliver comp

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