3 hours ago
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 secures AI. Okta is The World’s Identity Company. Freeing everyone to safely use any technology—anywhere, on any device or app.