- In this role, you will join the Agent Access Policies sub-team within Okta Secures AI as a Staff Machine Learning (ML) Engineer to advance Okta’s authorization capabilities

- By replacing static, rule-based systems with energetic AI security mechanisms, you will deliver real-time threat inspection, agent intent evaluation, and behavioral analysis—ensuring autonomous AI agents operate safely within specified bounds

- Implement intent-based enforcement to verify agent runtime requests match their intended purpose, requiring key capabilities

- Apply LLM reasoning and prompt parsing to interpret prompts, tool payloads, and intent in real time

- Integrate low-latency inference or semantic evaluation engines directly into the API gateway request path

- Use embeddings, vector search, or zero-shot classification to score alignment between agent intent and executed actions

- Design confidence-scored decision engines that feed semantic verification results into policy frameworks (e.g., Cedar)

- Establish evaluation benchmarks, prompt injection defenses, and guardrails to prevent bypasses or false positives

- Architect scalable ML and Generative AI systems integrating retrieval, inference, and evaluation pipelines

- Optimize prompting, context retrieval, and RAG workflows for accuracy, safety, and efficiency in Claude-based systems

- Build automated evaluation pipelines to measure model quality, correctness, groundedness, and safety in production

- Implement schema validation, structured output enforcement, and guardrails to ensure reliable, compliant AI outputs

Benefits





- Work from home opportunities

- Health + Wellness

- Financial Benefits

- Pay + Incentives

- Time Off

- Everyday Living
- Resources- Hands-on experience with modern Generative AI platforms (AWS Bedrock, OpenAI, Anthropic, etc.)

- Deep understanding of retrieval-augmented generation (RAG), embeddings, and knowledge-base workflows

- Experience building tools or infrastructure for AI/ML applications, with a deep understanding of the developer lifecycle in an AI-native world

- Proven ability to collaborate with product and engineering teams to drive greenfield initiatives forward, navigate unknowns, and iterate quickly and frequently

- Familiarity with ML frameworks (FastAPI, PyTorch, TensorFlow, Spark ML) and workflow orchestration tools (Airflow, etc.)

- Education:Bachelor’s or Master’s degree in Computer Science or related field

- Experience defining evaluation metrics, pipelines, and feedback loops for ML/GenAI systems

- 8+ years of software development experience, with strong programming expertise in Python (and familiarity with Go or Typescript a plus)

- Hands-on experience with applied machine learning, from feature engineering to training and fine-tuning models

- Hands-on experience with LiteLLM, LangGraph, LangChain, LlamaIndex, MCP, or other related AI agent frameworks

- Experience integrating AI-driven systems with identity, authentication, or security products

- Exposure to ethical AI, model risk, or compliance frameworks

- Familiarity with evaluation datasets, synthetic data generation, or LLM-as-a-judge methods

📌 Staff Machine Learning Engineer (SecureAI) (Toronto)
🏢 Okta
📍 Toronto