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.
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.
Furthermore, 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 at scale.
This 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:
1. 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.
2. 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.
3. 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.
4. 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.
5. 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.
6. Data Partnership & Governance Alignment
Ensure AI systems consume data through approved, governed interfaces that respect provenance, classification, and privacy-by-design principles.
7. Metrics, ROI & Business Outcomes
Define success metrics for enterprise AI adoption, including time from idea to deployed agent, cost efficiency, and business impact.
Measure revenue acceleration, productivity gains, and risk reduction attributable to AI-enabled workflows.
Produce clear, executive-level reporting that connects AI platform adoption to measurable business outcomes.
Job Requirements:
Experience: 7+ years in Cloud/Platform/Reliability Engineering, with 1-2 years specifically architecting secure AI/LLM systems at scale (RAG, model gateway, agent frameworks).
Cloud & Infra: Deep expertise in cloud platform security (AWS preferred), including IAM, KMS, container/Kubernetes security, and CI/CD hardening.
Engineering Skills: Hands-on engineering proficiency in at least one language (Python, Go, or TypeScript) to prototype controls, evaluators, or pipeline integrations.
Data Protection: Strong knowledge of classification, minimization, DLP, encryption, and privacy-by-design in AI contexts.
Preferred Qualifications:
Experience building enterprise platforms with cost controls and usage observability.
Experience implementing Zero Trust architecture and Infrastructure-as-Code (IaC).
Background in building secure RAG systems over governed enterprise data.
Familiarity with AI Security Posture Management (AI-SPM) and fleet-level visibility tools.
Experience with governance frameworks: NIST AI RMF, ISO/IEC 42001, and secure SDLC/LLMOps integrations.
Why This Role Matters:
AI is no longer a novelty; it is becoming core enterprise infrastructure. This role ensures Treasure Data moves beyond fragmented pilots to a unified, secure, and outcome-driven AI operating model that accelerates revenue, improves productivity, and manages risk at scale.
Role Scope & Boundaries:
The Principal Enterprise AI Platform Engineer is responsible for building and operating the enterprise AI platform that enables internal teams to safely design, deploy, and run AI agents and workflows for corporate business operations.
This role operates outside of the Treasure Data product development lifecycle and is distinct from Product Security, Application Security, or Cloud Infrastructure functions. It does not own security testing of customer-facing product features or the hardening of core product infrastructure. Instead, it owns the internal enterprise AI operating layer, the platforms, guardrails, and engineering patterns that make AI usable, scalable, and trustworthy across the organization.
While this role is not intended to be a permanent white-glove delivery function, it does provide targeted, high-leverage hands-on implementation in situations where:
A foundational reference architecture is required.
A high-risk or high-impact use case must be validated.
An initial build will accelerate broader adoption.
In these cases, the goal is to establish repeatable patterns and enablement, not ongoing ownership.
This role owns and delivers:
The enterprise AI platform and its reference architectures.
Reusable agent templates, patterns, and proof-of-concept implementations that demonstrate safe, scalable system design.
Technical ownership of the enterprise AI stack, working cross-functionally with IT, Security, Legal/Privacy, and business leaders to ensure adoption, reliability, and measurable outcomes.
Physical Requirements:
Working out of the Mountain View, California office according to our “Global Hybrid Working Policy.”
Travel Requirements:
May require up to 5% travel for team on-sites/ trips to other offices as needed for collaboration.
Perks and Benefits (US):
Our benefit package showcases our culture of care and empathy with
Comprehensive medical, dental, vision plans and Employee Assistance Program (EAP)
Competitive compensation packages
Company paid life insurance 3x salary
Company paid short- and long-term disability coverage
Retirement planning (401K) with 4% company match
Restricted Stock Units (RSU)
Flexible Time Off (FTO)
Up to 26 weeks paid parental leave including a post-partum night nurse
Comprehensive support and access to care for everyone, everywhere through Carrot - our global reproductive health and family-building benefit.
Our Dedication to You:
We value and promote diversity, equity, inclusion, and belonging in all aspects of our business and at all levels. Success comes from acknowledging, welcoming, and incorporating diverse perspectives.
Diverse representation alone is not the desired outcome. We also strive to create an inclusive culture that encourages growth, ownership of your role, and achieving innovation in new and unique ways. Your voice will be heard, and we will help amplify it.
Agencies and Recruiters:
We cannot consider your candidate(s) without a contract in place. Any resumes received without having an active agreement will be considered gratis referrals to us. Thank you for your understanding and cooperation!
- Department
- IT & Security
- Locations
- Mountain View, CA
- Remote status
- Hybrid
- Yearly salary
- $230,300 - $244,200
- Employment type
- Full-time
About Treasure Data
Treasure Data is the Intelligent Customer Data Platform (CDP) built for enterprise scale and powered by AI. Recognized as a Leader by Forrester and IDC, Treasure Data empowers the world’s largest and most innovative companies to deliver hyper-personalized customer experiences at scale that increase revenue, reduce costs, and build trust.
Through unique capabilities such as the Diamond Record, AI Agent Foundry, and AI Decisioning with Real-Time Personalization, Treasure Data enables marketing and CX teams to personalize cross-channel engagement in real-time, optimize marketing spend while increasing ROI, and drive customer lifetime value through more intelligent retention and loyalty.
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