Principal Enterprise AI Engineer

Treasure Data•Los Altos, CA

3h•Hybrid

About The Position

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.

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.

Nice To Haves

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.

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 that respect provenance, classification, and privacy-by-design principles.
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.

Benefits

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.

Stand Out From the Crowd

Upload your resume and get instant feedback on how well it matches this job.

Upload and Match Resume