Archived listing. The details below describe a past opening.
About Kinaxis
Are you looking to join an innovative, market-leading company where you can truly elevate your career? At Kinaxis we are serious about culture, we are serious about technology, we are serious about customers, and we are serious about not taking ourselves too seriously. If you are looking to be part of an incredible growth story, then we might just be the place for you!
In 1984, we started out as a team of three engineers. Today, we have grown to become a global organization with over 2000 employees around the world, 6 global office and a best-in-class HQ in Ottawa, Canada. As winners of several Top Employer awards globally, we are proud to work with our customers and employees towards solving some of the biggest challenges facing supply chains today.
Kinaxis is a global leader in modern supply chain orchestration, powering complex global supply chains, and supporting the people who manage them. Our powerful, AI infused platform provides full transparency and visibility across end-to-end supply chains, enabling our customers to make faster, better decisions. We are trusted by renowned global brands to provide the agility and predictability needed to navigate today’s volatility and disruption. With more than 40,000 users in over 100 countries, we are expanding our team as we continue to innovate and revolutionize how we support our customers.
About the team
The AI Innovation team builds Kinaxis operational orchestration: intelligence embedded in how an enterprise runs. It continuously senses what is changing, interprets what it means, decides what to do, and acts on it. Our focus is agents that reason about the problems an enterprise faces, decompose them, and orchestrate the models, tools, and deterministic engines that solve them.
Data and capable models are the starting point. The frontier is connecting signals to business context, decisions, and action, and that is where this team works. We sit at the intersection of applied research, product innovation, and customer impact, taking methods that are still being invented and engineering them into capabilities we test and deploy directly with customers.
Enterprise Agents are a new category of software with unique quality, reliability, observability, and security challenges. We will explore that frontier, learning the emerging methods and best practices for evaluating, monitoring, investigating, and improving AI Agents in a supply chain context.
Location
You must be in the Ottawa, Canada office at least three days a week.
Term Duration
This is a full-time, 8 or 12-month position, starting January, 2027.
Co-op / Intern Eligibility
This position is open to co-ops and interns. To be eligible, you must be currently enrolled in full-time education or be a recent/upcoming graduate within 12 months of the placement end date.
Compensation range
$27.04 - $39.66 hourly rate. The final offer within this range will reflect the candidate’s skills, year of education, and experience.
Vacancy Status
This is an existing job vacancy.
What you will do
You will work directly with a senior architect on the machinery and methodology behind how we evaluate, monitor, and investigate agentic AI systems. You will take on a scoped project within our AI assurance toolkit, which could focus on evaluation infrastructure, quality engineering, security analysis, or the practical tooling needed to understand agent behavior in real products. Example project areas include:
- Extend the harness, improving how evaluation runs are configured, executed, and reproduced, or building the tooling that makes results comparable across model, prompt, data, and version changes.
- Investigate how to make evaluation results meaningful: scoring and aggregation approaches, run-to-run variance, sample size, and what it takes to say with confidence that a change made things better.
- Research the landscape of agent evaluation tooling and techniques, and prototype the ideas worth adopting.
- Investigate security and trustworthiness questions for AI agents, such as how agents handle sensitive context, follow policies, resist unsafe instructions, recover from tool errors, and produce evidence that their actions can be reviewed.
- Build observability or investigation tools that help explain why an agent behaved the way it did, including trace analysis, failure categorization, regression detection, and clear reporting for engineering teams.
- Work in a GitHub-native, agentic engineering workflow, using AI-assisted development tools as part of your day-to-day toolkit.
- Share what you find. We will expect you to present your work to the team and to have opinions about it.
Day-to-day you will work with a team of experienced software engineers using modern tools and processes across quality engineering, AI evaluation, reliability analysis, and security-minded investigation.
What we are looking for
- Completed 3rd year of, or recently graduated from, a program in Software Engineering, Computer Engineering, Computer Science, or a related field.
- Demonstrated interest in software quality, reliability, security, or investigation-oriented engineering - through coursework, a previous work term, a personal project, research, or open-source contributions.
- Demonstrated interest in AI agents and their evaluation. This might look like experimenting with LLM APIs, building something with an agent framework, writing your own evals, or simply being able to talk in depth about why evaluating these systems is hard.
- Comfortable writing code in Python or a comparable language, and comfortable with Git and GitHub.
- Structured, curious, and skeptical in roughly equal measure. The core of this job is asking questions like “how would I know if this were wrong?”, “how could this fail?”, and “what evidence would convince someone else?” - then building the thing that answers them.
- Clear written communication. Evaluation results, incident findings, and security investigations are only useful if someone else can understand and trust them.
- Comfortable with ambiguity. Many of these problems do not have an established right answer yet, and you will help define the approach rather than follow a specification.
Nice to Have
- Experience with test automation frameworks, CI/CD pipelines, or property-based, fuzz, or metamorphic testing.
- Exposure to application security, threat modeling, policy testing, red-team style evaluation, secure software development, or responsible AI risk assessment.
- Exposure to LLM applications, RAG, prompt engineering, or agentic frameworks and their evaluation tooling.
- Familiarity with evaluation approaches such as LLM-as-judge, rubric-based scoring, or benchmark design, and an understanding of their limitations.
- Experience analyzing logs, traces, audit records, experiment results, or failure reports to identify patterns and explain system behavior.
- Experience with data manipulation and analysis, or with data quality and validation techniques.
- Exposure to knowledge graphs, semantic modeling, or ontologies.
- Any exposure to supply chain, logistics, manufacturing, or enterprise planning systems.
- Contributions to open-source projects, research, competitions, or hackathons
We’re accepting applications now through end of day on Sunday, October 4th, 2026. Please note that we may begin reviewing applications before the posting closes, so early submission is encouraged.
#Coop, #Internship, #Intern,
Work With Impact: Our platform directly helps companies power the world’s supply chains. We see the results of what we do out in the world every day, when we see store shelves stocked, when medications are available for our loved ones, and so much more.
Work with Fortune 500 Brands: Companies across industries trust us to help them take control of their integrated business planning and digital supply chain. Some of our customers include Lockheed Martin, Unilever, P&G, ExxonMobil, Cisco and more.
Social Responsibility at Kinaxis: Our Diversity, Equity, and Inclusion Committee weighs in on hiring practices, talent assessment training materials, and mandatory training on unconscious bias and inclusion fundamentals. Sustainability is key to what we do and we’re committed to a long-term net-zero operations strategy. We are involved in our communities and support causes where we can make the most impact.
People matter at Kinaxis and here are some of the perks and benefits we offer, which may vary by location and employee:
- Flexible vacation and Kinaxis Days (company-wide days off)
- Flexible work options
- Physical and mental well-being programs
- Regularly scheduled virtual fitness classes
- Mentorship programs, training, and career development
- Recognition programs and referral rewards
- Hackathons
For more information, visit the Kinaxis website at www.kinaxis.com or the company’s blog at http://blog.kinaxis.com.
Kinaxis welcomes candidates to apply to our inclusive community. We provide accommodations upon request to ensure fairness and accessibility throughout our recruitment process for all candidates, including those with specific needs or disabilities. If you require an accommodation, please reach out to us at recruitmentprograms@kinaxis.com. This contact information is for accessibility requests only and cannot be used to inquire about the status of applications.
Kinaxis is committed to ensuring a fair and transparent recruitment process. We use artificial intelligence (AI) tools in the initial step of the recruitment process to compare submitted resumes against the job description to identify candidates whose education, experience, and skills most closely match the requirements of the role. After the initial screening, all subsequent decisions regarding your application, including final selection, are made by our human recruitment team. AI does not make any final hiring decisions.
