AI Automation Engineer

Fortinet secures enterprise, service provider, and government organizations worldwide through its Fortinet Security Fabric cybersecurity platform. The company is seeking a Junior AI Automation Engineer to build and maintain a technical interview pipeline covering question management, AI-assisted scoring, quality validation, fairness monitoring, and end-to-end workflow automation.

What you'll do:

• We're looking for a junior engineer to be the primary engineer building and maintaining our technical interview pipeline - from the question bank to AI-assisted scoring to full workflow automation - working alongside the team to grow this role into a broader automation function over time. This isn't a "call an API and ship it" job: you'll be designing the systems that add/calibrate interview questions and evaluate candidate answers, which means understanding how to prompt and structure AI models for consistency, how to measure and validate output quality against ground truth, and how to catch and correct the ways these systems get things wrong. This is a role we expect to grow - the shape of that growth is still being defined
• Add, revise, and retire technical interview questions across roles/levels/skill areas
• Maintain question metadata (difficulty, topic tags, expected answer criteria, role relevance)
• Create variant/randomized versions of questions to reduce answer-sharing risk
• Build validation checks (automated and manual) to catch incorrect, ambiguous, or miscalibrated questions before they enter the repository
• Build automation to update problem sets and recalculate average difficulty ratings as new results come in
• Review and update questions periodically to prevent leakage/staleness and keep content aligned with actual job requirements
• Architect scoring workflows that evaluate and compare candidate answers against reference answers/rubrics, grounded in a clear methodology for what "correct" and "well-scored" mean
• Calibrate and benchmark scoring prompts/models against human-graded samples, measuring accuracy and identifying systematic errors or bias
• Understand and account for model failure modes (inconsistency, hallucination, prompt sensitivity) and design safeguards around them
• Flag edge cases or low-confidence scores for human review rather than fully automating high-stakes decisions
• Automate the end-to-end workflow: question selection -> test delivery -> answer collection -> scoring -> reporting

What they're looking for:

• - Bachelor's degree in Computer Science or related field, or equivalent practical experience
• - Solid programming fundamentals (Python, JavaScript/TypeScript, or similar)
• - Comfort working with APIs, including LLM/AI APIs (OpenAI, Anthropic, etc.)
• - Demonstrated experience designing and evaluating prompts/pipelines for LLM-based tools (not just using AI products, but building with them)
• - Proficient with Git and a hosted platform (GitHub or GitLab) - branching, PRs/MRs, code review, CI basics
• - Basic understanding of databases (SQL or similar)
• - Strong attention to detail and technical writing ability
• - Ability to work independently on processes that are still being defined, and adapt as scope evolves
• Must be authorized to work in the U.S. without sponsorship
• - Familiarity with test/assessment platforms or ATS integrations
• - Exposure to scripting automation (e.g., workflow tools, cron jobs, CI-style pipelines)
• - Interest or coursework in fairness/bias in ML systems

Benefits:

• Medical, dental, vision, life and disability insurance
• 401(k)
• 11 paid holidays
• Vacation time
• Sick time
• A comprehensive leave program
• All roles are eligible to participate in the Fortinet equity program.
• Bonus eligibility is reviewed at the time of hire and annually at the Company’s discretion.
• Hybrid workplace