Principal Engineer - AI Systems

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 you'll 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.

• 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
• Bachelor's or Master's 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