Principal Machine Learning Engineer

Okta is hiring a Principal Machine Learning Engineer (Okta Secures AI) to evolve authorization for agent access policies using dynamic AI security mechanisms.

Responsibilities

• Build intent-based enforcement to confirm agent runtime requests match intended purpose
• Apply LLM reasoning and prompt parsing to interpret prompts, tool payloads, and intent in real time
• Integrate low-latency inference or semantic evaluation engines 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 such as Cedar
• Establish evaluation benchmarks , prompt injection defenses , and guardrails to prevent bypasses or false positives
• Architect scalable ML and Generative AI systems with 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 for reliable, compliant AI outputs
• Mentor and coach engineers to support team and community growth

Requirements

• 10+ years of software development experience with strong Python expertise; Go or TypeScript familiarity is a plus
• Hands-on experience with applied machine learning, including feature engineering , training , and fine-tuning models
• Hands-on experience with modern Generative AI platforms such as AWS Bedrock , OpenAI , Anthropic , etc.
• Deep understanding of retrieval-augmented generation (RAG) , embeddings , and knowledge-base workflows
• Hands-on experience with AI agent frameworks including LiteLLM , LangGraph , LangChain , LlamaIndex , MCP , or similar
• Familiarity with ML frameworks such as FastAPI , PyTorch , TensorFlow , and Spark ML , plus orchestration tools like Airflow
• Experience defining evaluation metrics , pipelines, and feedback loops for ML/GenAI systems
• Proven ability to collaborate with product and engineering teams to drive greenfield initiatives , manage unknowns, and iterate quickly
• Experience building tools or infrastructure for AI/ML applications with deep understanding of the developer lifecycle in an AI-native world

Technologies

• Python, Go, TypeScript
• AWS Bedrock, OpenAI, Anthropic
• LiteLLM, LangGraph, LangChain, LlamaIndex, MCP
• FastAPI, PyTorch, TensorFlow, Spark ML
• Airflow, Cedar
• Claude-based systems

Location & Salary

• San Francisco, CA (hybrid)
• USD 238,000 - 326,000 per yearly

Education

• Bachelor’s or Master’s degree in Computer Science or related field

Benefits

• Equity (where applicable), bonus, and benefits including health, dental and vision insurance
• 401(k)
• Flexible spending account
• Paid leave including PTO and parental leave

Extra Credit

• 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

Okta Experience

• Supporting Your Well-Being
• Driving Social Impact
• Developing Talent and Fostering Connection + Community