Principal Full-Stack AI Engineer - Hybrid

Role overview

Responsibilities

• Design core architecture, frameworks, and shared services for enterprise AI platforms and agent ecosystems.
• Develop model orchestration, lifecycle management, governance, observability, and memory services.
• Create reusable tools, patterns, and automation for AI agent development and deployment.
• Set cloud-native engineering, security, CI/CD, infrastructure-as-code, and reliability practices.
• Mentor engineers and provide technical leadership through architecture reviews.

Required qualifications

• Extensive experience building and operating large-scale production software platforms.
• Strong Python expertise and at least one additional language such as Go, Java, or TypeScript.
• Hands-on Kubernetes, containers, Terraform, CI/CD, and cloud-native architecture experience.
• Deep knowledge of generative AI, LLMs, agent frameworks, RAG, orchestration, and AI platform technologies.
• Experience implementing security, governance, observability, and enterprise-scale platform controls.
• Ability to lead complex technical initiatives and influence engineering strategy.

Preferred qualifications

• Google Cloud Platform experience, including GKE, Vertex AI, BigQuery, and IAM, is beneficial.
• Multi-agent systems, AI governance, and model lifecycle experience are beneficial.
• Familiarity with MLflow, OpenTelemetry, Delta Lake, Iceberg, Ray, DeepSpeed, or vLLM is beneficial.
• Enterprise AI platforms, developer enablement frameworks, and mentoring experience are beneficial.

Compensation

• Annual salary range is $140,000–$160,000, depending on experience and qualifications; the role is also eligible for a discretionary annual incentive.

Benefits

• Benefits include medical, dental, vision, and life insurance; paid holidays and time off; 401(k); disability coverage; paid parental leave; and an employee stock purchase plan.