AI Trainer

Okta•Toronto, ON

9h•CA$124,000 - CA$186,000•Hybrid

About The Position

Secure Every Identity, from AI to Human. Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. The Team You'll be joining our Okta Customer Acceleration organization, a high-impact team focused on defining and optimizing the self-service journey for our customers across Knowledge, Online Support, and Communities. Our mission is to transform the customer experience by enabling efficient, accurate, and engaging self-service solutions. The Opportunity We're looking for an experienced AI Trainer and Optimization Analyst to take full ownership of our customer support agentic experiences. This is a critical specialist role that offers the chance to directly influence millions of customer interactions annually. You will act as the primary expert on the AI agent's performance, applying a strategic mindset to continuously analyze conversational data and leverage analytics to enhance the bot's ability. You will be responsible for: Implementing prompt engineering best practices. Ensuring the agent provides accurate, efficient, and on-brand support. Managing the bot's tone and ethical guardrails to prevent hallucination and incorrect assumptions. "Thinking bigger" to bring new, strategic ideas for leveraging the agentic experience for maximum customer impact.

Requirements

Deep Conversational AI Experience: Proven experience in a role involving AI training, prompt engineering, Natural Language Processing (NLP), or conversational design, specifically for customer support or enterprise service systems.
Analytical Rigor: Strong analytical skills with a proven ability to interpret large sets of conversational data and performance metrics to draw meaningful, actionable insights for AI training and system tuning.
Platform Proficiency: Familiarity with major AI conversational platforms (e.g., Dialogflow, IBM Watson, Rasa, or similar enterprise-level tools).
Technical Communication: Excellent written communication skills, with a keen eye for detail and the ability to write clear, concise, and helpful responses that maintain a professional tone.
Ecosystem Understanding: Ability to understand the broader online customer support ecosystem, ensuring an integrated and seamless omnichannel experience when handing off between the bot and human agents.
Strategic Mindset: A proactive, problem-solving approach with the ability to "think bigger" and bring new, strategic ideas for leveraging the agentic experience for maximum customer impact.

Responsibilities

Own Conversational Quality & Tone: Act as the primary owner for the AI agent's output, managing the content, tone, and ethical guardrails to ensure responses are accurate, on-brand, and avoid inappropriate or incorrect assumptions and "hallucination."
Prompt Engineering & Training: Develop, test, and deploy advanced prompt engineering techniques, training materials, and conversational flows to enhance the AI agent's accuracy, intent recognition, and overall effectiveness.
Performance Analysis & Optimization: Proactively monitor and analyze AI agent performance metrics, including deflection rates, resolution rates, and customer satisfaction (CSAT) scores, translating data into actionable training and optimization plans.
Gap Identification & Remediation: Review and categorize high-volume AI conversations to identify new customer intents, common misclassifications, and critical content gaps in the knowledge base that require remediation.
Strategic Collaboration: Work closely with the Content, Knowledge, and Customer Experience teams to understand common customer issues and translate those insights into strategic AI training plans, focusing on high-ticket volume areas.
Continuous Improvement: Maintain and update conversation scripts to reflect product and policy changes, and continuously identify and report on agent bugs, system gaps, and areas for potential escalation.
Thought Leadership: Stay current with the latest trends and technologies in conversational AI, machine learning, and prompt engineering, bringing new ideas and strategic proposals to the table.