Principal Enterprise AI Engineer

Treasure Data

At Treasure Data, we’re on a mission to radically simplify how companies use data and AI to create connected customer experiences. Our intelligent customer data platform (CDP) drives revenue growth and operational efficiency across the enterprise to deliver powerful business outcomes.

Overview

We are thrilled that Forrester has recognized Treasure Data as a Leader in The Forrester Wave™:
Customer Data Platforms For B2C. It's an honor to be acknowledged for our efforts in advancing the CDP industry with cutting-edge AI and real-time capabilities. Treasure Data employees are enthusiastic, data-driven, and customer-obsessed. We are a team of drivers—self-starters who take initiative, anticipate needs, and proactively jump in to solve problems. Our actions reflect our values of honesty, reliability, openness, and humility.

Your Role

The Principal Enterprise AI Engineer is a senior individual contributor responsible for end-to-end ownership of the enterprise AI platform. This role designs, builds, and operates the foundational AI capabilities, platforms, agent frameworks, guardrails, and tooling that enable both technical and non-technical teams to build and maintain AI-powered workflows safely and s is a hands‑on builder role. You will set the technical vision and implement it.

You will partner closely with the CIO/CISO, Security Architecture, Trust & Assurance, Security Operations, IT Operations, Legal/Privacy, and business leaders across GTM, R&D, and G&A. Success is measured by business adoption, time-to-value, platform reliability, cost efficiency, and controlled risk.

Responsibilities

• Enterprise AI Platform Ownership

• Own the design, build, and operation of the enterprise AI platform, including LLM access and routing, agent orchestration frameworks, and secure RAG architectures over governed enterprise data.

• Define and maintain reference architectures and paved roads that standardize how AI is built, deployed, and operated across the enterprise.

• Ensure platform scalability, reliability, and consistent operation across NA, EMEA, Japan, and APAC, accounting for regional regulatory and data residency requirements.

• Platform Engineering & Agent Lifecycle Management

• Build reusable platform components such as agent templates, workflow patterns, and configuration and version management capabilities.

• Implement automated evaluation, logging, and observability pipelines that support production‑grade AI systems.

• Own the enterprise AI agent lifecycle, including versioning, upgrades, reliability standards, deprecation, and clear ownership handoff to consuming teams.

• Embed cost visibility, usage controls, and to ensure reliability, compliance, and ROI by default.

• Enterprise Enablement & Adoption Acceleration

• Partner with GTM, R&D, and G&A leaders to identify and prioritize high‑impact AI use cases aligned to revenue, margin, cost, and productivity goals.

• Translate business workflows into scalable, repeatable AI agent patterns suitable for enterprise adoption.

• Enable teams through reference implementations, documentation, office hours, and pragmatic guidance that replaces blanket restrictions with safe, supported paths forward.

• Drive phased adoption of the enterprise AI platform, balancing experimentation with operational readiness and organizational change management.

• AI Tooling & Ecosystem Stewardship

• Evaluate and select AI tools across the enterprise ecosystem based on capability, risk, cost, and operational fit.

• Define clear guidance for experimentation versus production usage of AI tools.

• Reduce tool sprawl and fragmentation while preserving appropriate team autonomy.

• Serve as the technical steward of the enterprise AI platform and tooling stack.

• Security, Risk & Compliance by Design

• Partner with Security Architecture to identify and mitigate AI‑specific threats, and embed security and privacy controls into the AI platform by default.

• Align enterprise AI usage with ISO, SOC2, HIPAA, and emerging AI governance frameworks such as NIST AI RMF and ISO/IEC 42001.

• Data Partnership & Governance Alignment

• Ensure AI systems consume data through approved, governed interfaces…