Principal AI Engineer

***This role is onsite in San Bruno, CA relocation is offered*** As a Principal Engineer, AI Systems in the Design Organization, you will: Implement and Productionize AI Systems: Partner with design, product, and engineering leaders to translate the AI roadmap into scalable, secure, and resilient solutions that meet the needs of the Design Organization. Drive AI Innovation: Identify and deliver high-impact opportunities where generative AI, LLMs, and intelligent automation can enhance creative workflows, product discovery, design quality, and speed. Build and Scale Production Services: Develop reliable backend services in Python and Node.js, focusing on performance, resilience, and observability. Harden prototypes into production-ready, secure, and scalable services within approved infrastructure and guardrails. Ensure seamless integration with identity, networking, data platforms, observability, and compliance controls (e.g., SSO, secrets management, service mesh). Define Production-Readiness: Establish gates for POCs, including SLA/SLO targets, error budgets, performance baselines, cost limits, capacity planning, disaster recovery, and runbooks. Operational Excellence: Drive CI/CD pipelines, infrastructure as code, and migration of prototypes to dev, stage, and prod environments. Ensure operational ownership with alerting, on-call strategies, incident response, and continuous improvement. Architect AI-Powered Design Tools: Lead the technical design and architecture of internal tools and subsystems that empower designers, researchers, and content strategists. Build scalable, reusable infrastructure for organization-wide AI applications. Mentor and Uplift Technical Craft: Guide engineers and architects through complex architecture decisions, rapid prototyping, and AI tool selection. Foster a culture of experimentation, technical excellence, and responsible innovation. Promote AI Thought Leadership: Represent the Design Organization in internal AI communities, share learnings, and influence AI adoption. What youll bring: Programming: Expert in Python and Node.js for backend services, data pipelines, and AI integration. Kubernetes & Cloud-Native: Deep experience with Kubernetes, Helm/Kustomize, GitOps (Argo CD/Flux), service mesh (Istio/Linkerd), autoscaling, security, and cost optimization. CI/CD & Infrastructure: Proficient with Jenkins (or equivalent), Terraform/CloudFormation, blue-green/canary deployments, feature flags, automated testing, and rollback strategies. Data & Storage: Strong experience with SQL (Postgres, MySQL, SQL Server, Snowflake) and NoSQL (DynamoDB, MongoDB, Cassandra, Redis, Elasticsearch) databases, including schema design, optimization, and scaling. Familiarity with vector databases and embedding stores. APIs & Integration: Skilled in REST and GraphQL, secure service-to-service authentication, rate limiting, quotas, and event streaming (Kafka/Pub/Sub). Observability: Experience with Prometheus, Grafana, tracing, metrics, log aggregation, SLOs, error budgets, and incident response. Minimum Qualifications: 12+ years in software or platform engineering, delivering production systems at scale 7+ years combined professional experience in Python and Node.js (minimum 4+ years in each) 4+ years operating workloads in Kubernetes in production 5+ years designing and operating both SQL and NoSQL data models 2+ years building or operating ML/LLM-powered applications in production 5+ years leading cross-functional architecture and mentoring senior engineers Bachelors or Masters in Computer Science or related field, or equivalent practical experience Strong communication skills and a portfolio of shipped systems with measurable impact #app #LI-MS3 #LI-Onsite