Principal Software Engineer, AI (Web & Data)

Okta•Toronto, ON

18h•$175,000 - $192,500•Hybrid

About The Position

This role is for an accomplished Principal Engineer to lead the technical architecture and evolution of Okta's hybrid digital ecosystem. The engineer will drive the strategic integration of multi-modal AI into core infrastructure and architect an omnichannel platform for complex customer journeys. This involves balancing the adoption of third-party AI solutions (OpenAI, Anthropic) with proprietary optimizations. The role requires a technical leader who champions a vendor-agnostic, ethically grounded, and Privacy by Design approach to AI implementation.

Requirements

8–10 years in software engineering, specializing in SaaS platform architecture and distributed systems design.
Excellence in technical diplomacy and stakeholder influence.
Proven ability to translate complex AI/Data roadmaps into business value while mentoring senior teams and advocating for architectural best practices.
Strong hands-on experience with Apache Airflow (or similar), Kafka, and dbt to support real-time AI applications.
Proven expertise integrating LLMs into production web environments with a focus on agentic workflows and autonomous UI generation.
Deep understanding of headless CMS, composable, and event-driven patterns that allow for programmatic content and UI generation.
Experience with cloud-native technologies (AWS/GCP, Docker, Kubernetes).
Deep expertise in data privacy frameworks and AI ethics.

Responsibilities

Lead the roadmap for migrating legacy data pipelines to AI-native architectures.
Design modern data orchestration solutions utilizing Apache Airflow, dbt, and Kafka to replace outdated batch processing with real-time, event-driven flows.
Define the web infrastructure required for a high-agility ecosystem.
Architect the evolution of Headless CMS environments (AEM, Contentful) and modern frontend frameworks to enable automated page assembly and AI-driven UI components.
Design and build autonomous pipelines that bridge the gap between design systems, automated component development, and publishing workflows.
Establish standards for RAG, vector databases, and LLM orchestration.
Provide architectural guidance for the seamless integration of AI capabilities across headless and omnichannel systems while ensuring consistency, performance, and security.
Champion the use of AI-assisted coding and engineering productivity tools such as Claude Code and Cursor to accelerate development cycles and optimize architectural decision-making.