Principal Applied AI Marketing Engineer

Okta Okta · Enterprise · San Francisco, CA · Marketing Leadership-455

Okta is seeking a Principal Applied AI Marketing Engineer to be a hands-on builder within the Marketing AI Spoke team. This role will function as the primary product owner and technical implementer for AI agents, workflows, and low-code/no-code applications, responsible for the full engineering lifecycle from definition to deployment. The position requires a blend of marketing acumen, technical aptitude, and problem-solving skills to translate business challenges into deployed AI solutions, with a focus on improving marketing productivity and operational efficiency.

What you'd actually do

  1. Marketing AI Solution Development: Patterning with TDI leveraging company-wide approved platform. Design, build, and maintain the underlying infrastructure and services required to run scalable AI applications for the Marketing organization. This includes connecting data sources, building APIs, developing front-end user interfaces (UI/UX), and engineering the backend logic.
  2. AI Agent & Workflow Engineering: Architect, code, test, and deploy AI agents and low-code/no-code workflows that solve critical marketing challenges. Ensure solutions are robust, secure, and seamlessly integrated into the existing AI stack (e.g., CRM, MAP, CMS).
  3. Agentic Strategy & Architectural Design: Act as the technical leader for your assigned portfolio, defining the architectural blueprints for new AI enabled workflows. Evaluate and recommend the appropriate technical tooling (e.g., cloud services, databases, low-code platforms) to maximize performance and minimize operational costs.
  4. Data and Prompt Engineering: Partner with data science and marketing ops teams to ensure data pipelines support AI application needs (RAG, fine-tuning). Design and iterate on effective prompts and input-output schemas to optimize the performance and reliability of large language model (LLM) agents.
  5. Value Measurement & System Optimization: Implement performance tracking directly into deployed platforms (instrumentation). Use technical metrics (latency, uptime, error rates) and business metrics (ROI, time saved) to justify system improvements and guide the marketing AI roadmap.

Skills

Required

  • AI/ML
  • engineering
  • product ownership
  • technical implementation
  • marketing acumen
  • problem-solving
  • infrastructure and services
  • scalable AI applications
  • data sources
  • APIs
  • front-end user interfaces (UI/UX)
  • backend logic
  • AI agents
  • low-code/no-code workflows
  • robust solutions
  • secure solutions
  • AI stack integration
  • architectural design
  • technical tooling
  • cloud services
  • databases
  • low-code platforms
  • performance optimization
  • cost minimization
  • data pipelines
  • RAG
  • fine-tuning
  • prompt engineering
  • input-output schemas
  • LLM agents
  • performance tracking
  • instrumentation
  • technical metrics
  • business metrics
  • ROI
  • time saved
  • system improvements
  • marketing AI roadmap

Nice to have

  • marketing operations
  • marketing strategy
  • tools/platforms for large-scale marketing organizations

What the JD emphasized

  • primary product owner
  • technical implementer
  • AI agents
  • workflows
  • low-code/no-code applications
  • full engineering lifecycle
  • deployed AI-driven solutions
  • AI Agent & Workflow Engineering
  • Agentic Strategy & Architectural Design
  • Data and Prompt Engineering
  • LLM agents

Other signals

  • AI agents
  • workflows
  • low-code/no-code applications
  • full engineering lifecycle
  • deployed AI-driven solutions