Job Description:
The Staff Engineer, AI Engineering is a senior individual contributor responsible for translating the enterprise AI engineering roadmap into scalable platform architecture, reusable technical patterns, and production-grade shared services. Reporting to the Director, AI Engineering, this role provides deep technical leadership across AI enablement, responsible AI controls, observability, cost attribution, and reusable component strategy. The Staff Engineer acts as the connective technical tissue across Engineering, IT, Security, Legal, Data, and business unit teams - setting standards, creating reference implementations, and guiding teams toward consistent, secure, measurable AI adoption without relying on direct authority.
What you'll do:
AI Platform Architecture & Standards
- Define and evolve enterprise AI architecture patterns for LLM integration, retrieval-augmented generation (RAG), agentic workflows, prompt orchestration, and workflow automation.
- Create reference architectures, design reviews, and implementation guidance that enable consistent AI development across business units.
- Serve as a technical authority for AI platform decisions, including model selection, integration approaches, and data boundary enforcement.
- Evaluate emerging AI technologies and recommend fit-for-purpose adoption paths aligned to security and enterprise architecture requirements.
Reusable Components & Shared Services
- Design and build reusable AI components such as connectors, agents, skill templates, prompt libraries, and service APIs.
- Lead technical design for shared platform services for AI observability, logging, usage metering, and lifecycle management.
- Establish quality, versioning, and contribution standards for the shared AI component catalog.
Responsible AI Engineering & Governance
- Architect engineering controls for access management, data classification enforcement, prompt safety, output validation, and audit logging.
- Partner with Security, Legal, and compliance stakeholders to embed responsible AI requirements into development and deployment pipelines.
- Build technical dashboards and telemetry that expose adoption, risk, performance, and governance compliance across AI-enabled systems.
Productivity, Measurement & Technical Leadership
- Develop AI-assisted workflow patterns that improve individual productivity, knowledge retrieval, and task automation.
- Partner with Finance and platform teams to develop cost metering, showback/chargeback, and optimization mechanisms for AI services.
- Mentor senior and mid-level engineers and lead complex cross-functional technical initiatives from concept through production.