2 months ago
Toronto, CanadaStaff+
Responsibilities
- Architect, design, and deploy robust machine learning and generative AI systems integrated with platform services.
- Establish scalable LLMOps pipelines and infrastructure for large-scale generative AI use cases.
- Lead initiatives to tune, optimize, and deploy secure, reliable, and performant agentic applications.
- Design scalable and observable ML and generative AI systems incorporating retrieval, inference, and evaluation pipelines.
- Develop structured prompting, context retrieval, and RAG workflows for Claude-based systems.
- Build automated evaluation pipelines measuring model quality, correctness, groundedness, and safety in production.
- Implement schema validation, structured output enforcement, and other AI guardrails for reliable, auditable, and compliant outputs.
- Partner with Product, Security, Platform Engineering, product managers, researchers, and engineers to deliver AI-powered experiences.
- Drive technical decisions balancing simplicity, flexibility, reliability, and performance.
- Mentor and coach engineers and contribute to the broader engineering community.
Requirements
- 7+ years of software development experience and strong programming expertise in Python; Go or TypeScript familiarity is a plus.
- Hands-on experience with applied machine learning, including feature engineering, model training, and fine-tuning.
- Hands-on experience with generative AI platforms such as AWS Bedrock, OpenAI, and Anthropic.
- Deep understanding of retrieval-augmented generation, embeddings, and knowledge-base workflows.
- Experience with LiteLLM, LangGraph, LangChain, LlamaIndex, MCP, or related AI agent frameworks.
- Familiarity with FastAPI, PyTorch, TensorFlow, Spark ML, and workflow orchestration tools such as Airflow.
- Experience defining evaluation metrics, pipelines, and feedback loops for ML and generative AI systems.
- Experience building tools or infrastructure for AI/ML applications and understanding the developer lifecycle in an AI-native environment.
- Ability to collaborate with product and engineering teams, drive greenfield initiatives, navigate ambiguity, and iterate quickly.
- Preferred experience integrating AI-driven systems with identity, authentication, or security products.
- Preferred exposure to ethical AI, model risk, compliance frameworks, evaluation datasets, synthetic data generation, or LLM-as-a-judge methods.
Benefits
- Annual base salary range of $168,000–$231,000 CAD for candidates located in Canada.
- Health, dental, and vision insurance.
- RRSP with a match, healthcare spending, telemedicine, and paid leave including PTO and parental leave.
- Hybrid work arrangement, with an immersive in-person onboarding experience.
- Equity and bonus opportunities where applicable.
Tech Stack
Categories
About Okta
Okta builds cloud-based identity and access management for enterprises and developers, including single sign-on, multi-factor authentication, and lifecycle management. It sells subscription SaaS as the Okta Workforce Identity and Customer Identity Clouds; the latter incorporates Auth0, acquired in 2021. Founded in 2009 and headquartered in San Francisco, Okta is a public company traded on Nasdaq.