AI Platform Engineer

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 an AI Platform Engineer on AI Mining, you'll own the data infrastructure layer that makes skill mining possible. That means BigQuery datasets and schemas, cloud storage, service accounts and IAM, Vertex AI pipeline infrastructure, Dataform integration, and the event streaming resources that connect mining outputs to the rest of the platform. It also means building the automated pipelines that move data into place — scheduled jobs, data copy pipelines, backfill orchestration — so the right data is where it needs to be when the mining team needs it. You'll work at the intersection of data engineering and infrastructure — your work is what AI engineers, data scientists, and product engineers stand on when they ship. What you'll do Get oriented on the data infrastructure landscape: BigQuery datasets and schemas, cloud storage, IAM surface, Vertex AI pipeline setup, Dataform integration, and event streaming topics. Be paired with a peer and your manager — you'll have context and support before you're expected to own anything independently. You'll be exposed to the open source technologies we depend on. We employ many open source tools to get the job done, and we love to contribute back to those communities. Ship your first infrastructure changes: a new dataset, a storage resource, an IAM policy, or a schema update that unblocks the mining team. Own core data infrastructure: BigQuery datasets, preprocessing storage buckets, service accounts, and access policies across environments. Partner with AI and data science engineers to translate new pipeline and data needs into provisioned, governed infrastructure. Contribute to data quality checks, freshness monitoring, and anomaly detection for mining inputs and outputs. Strengthen the team's infrastructure-as-code practices (Terraform, CI/CD). Drive expansion of the data platform as the team grows into new channels, customer segments, and verticals. Own the data governance posture: retention, anonymization, opt-out handling, and access separation for privacy-sensitive content. Be a trusted partner for AI, backend, product, and analytics teams — they rely on you for reliable data contracts and predictable infrastructure. Skills you'll bring You have strong experience in data engineering, data platform, or infrastructure work with a data focus. You're deeply comfortable with BigQuery or a comparable cloud data warehouse — schema design, dataset management, and access governance feel natural. You have hands-on experience with infrastructure-as-code; you've provisioned cloud resources and know what good looks like. You think in data contracts — freshness, lineage, quality, and downstream dependencies. You're comfortable with privacy-sensitive data: you understand why retention policies, anonymization, and access separation matter and how to implement them correctly. You work well across ambiguity — teams come to you with a data need, and you can turn it into a concrete, durable infrastructure plan. You measure and monitor everything. You're not done when it's provisioned; you're done when it's observable. You enjoy working on a distributed team and value async communication as much as in-person collaboration. Why Join Dialpad Work a