We are a startup vibe work culture, where we are highly ambitious to grow fast and big. Keep reading only if that kind of environment interests you. If you are looking for a highly structured, large enterprise, this is not the right position.

Talos is looking for an AI Builder who is genuinely excited about where artificial intelligence is going and wants to spend their time figuring out how to put it to work.

This is not a traditional software developer role and it is not an AI research position.

We are looking for someone who experiments with AI because they are naturally curious about it. You probably follow new models, agents, tools, frameworks, and capabilities as they emerge. You test things yourself. You build things nobody asked you to build. You see repetitive work and immediately start wondering whether it could be automated.

Your job will be to explore what is becoming possible with AI and turn the strongest opportunities into practical tools, workflows, agents, automations, and software used inside Talos.

You will work directly with leadership and our software team, initially focusing heavily on our training division, TrueTraining.ca.

- WHY THIS OPPORTUNITY IS DIFFERENT Most technology roles give you an established system and ask you to improve one part of it.

This role starts earlier.

You will help Talos determine what is now possible because of AI.

That could mean

- Building an agent that completes part of an operational process
- Connecting an LLM to company data
- Giving an internal system the ability to reason over documents
- Automating work currently completed manually
- Testing whether a new model can solve a problem that was not practical 6 months ago
- Building an internal AI tool from scratch
- Connecting software, APIs, databases, and AI into a new workflow
- Rapidly prototyping an idea to determine whether it deserves further investment

Talos already has real operations, company data, internal software, a development team, and workflows across training, technology, staffing, and the public sector. You will have real problems to solve and real users to build for.
- THE QUICK SUMMARY Your goal is simple: Find useful ways to apply AI across the team.

You will

- Identify work that AI could perform better, faster, or differently
- Build prototypes quickly
- Connect AI with company data and existing systems
- Build agents and automated workflows
- Work with APIs, databases, integrations, and internal applications
- Test whether AI outputs are actually accurate and useful
- Turn successful experiments into reliable operational systems
- Share discoveries, risks, and opportunities with leadership and the software team

You do not need to arrive knowing how to build everything. You do need to be unusually good at figuring things out.
- WHAT YOU WILL OWN You will have significant freedom to investigate AI opportunities throughout the company.

Your work may include

- Testing new models and understanding what they are actually good at
- Building agents that complete multi step tasks
- Creating AI powered workflows and automations
- Connecting large language models with internal company information
- Working with APIs and external services
- Building lightweight applications and internal tools
- Experimenting with Model Context Protocol and emerging AI infrastructure
- Working with databases and company data
- Comparing models for accuracy, reliability, speed, and cost
- Finding failure cases and improving system behaviour
- Building evaluations to determine whether something actually works
- Designing human review and escalation where appropriate
- Working with developers when an experiment needs deeper engineering
- Demonstrating promising ideas to leadership
- Turning successful prototypes into operational tools





You should be the type of person who encounters a tool, API, or technical problem you have never seen before and starts figuring it out rather than waiting for someone to teach you.
- BUILD FAST. DEPLOY CAREFULLY. We expect you to prototype aggressively.

Many ideas should be tested quickly. Some will work. Some will fail. Some should be abandoned within hours.

That is part of the job.

Once something proves valuable enough to enter real operations, the standard changes.

Accuracy, security, privacy, reliability, access controls, monitoring, maintainability, documentation, and failure handling matter.

The goal is not to produce impressive demonstrations.

The goal is to discover useful capabilities quickly and turn the right ones into systems people can actually rely on.

- WHAT SUCCESS LOOKS LIKE Strong performance means Talos is continuously discovering and implementing useful applications of AI.

Success looks like

- New AI capabilities are tested quickly instead of being discussed for months
- Good ideas become working prototypes
- Strong prototypes become tools used by real employees
- Manual work is reduced through intelligent automation
- Existing systems become more capable because AI is integrated into them
- AI systems securely use relevant company information
- Experiments have clear measures of whether they worked
- Outputs are tested rather than assumed to be correct
- Failed ideas are identified quickly
- Useful discoveries are shared across the software team
- Leadership understands which new AI capabilities could materially affect Talos
- The company becomes progressively better at using AI as the technology evolves

Leadership should be able to bring you a problem and expect you to investigate whether AI can meaningfully solve it. Just as importantly, you should regularly bring opportunities to leadership that nobody asked you to investigate.
- WHO WILL DO WELL HERE This role is built for someone who genuinely likes AI.

Not because it is popular.

Because you find the technology interesting enough that you are already experimenting with it.

You may be someone who:

- Regularly tests new AI products and models
- Follows developments in agents, LLMs, multimodal AI, coding agents, automation, and emerging tooling
- Gets curious when a new model or capability is released
- Has built something simply because you wanted to know whether it was possible
- Uses AI extensively in your own work
- Constantly looks for better ways to accomplish things
- Learns technical concepts independently
- Is comfortable opening documentation and figuring things out
- Likes solving poorly defined problems
- Moves quickly from an idea to something testable
- Can recognize when exciting technology is not actually useful
- Takes responsibility for getting to a working result
- Is comfortable working in a startup style environment

Formal experience matters less to us than evidence that you can learn, experiment, build, and solve problems.
- THE TECHNICAL BAR Using ChatGPT heavily is not enough.

You should be capable of building with AI, not just using AI products.

That may include experience building:

- AI agents
- Automations
- API integrations
- Internal tools
- Web applications
- AI powered workflows
- Retrieval systems
- Model integrations
- Data pipelines
- Software that uses LLM APIs

Experience with some of the following would be valuable:
- OpenAI, Anthropic, Gemini,



or similar model APIs
- Tool calling and structured outputs
- Model Context Protocol
- Retrieval augmented generation
- AI evaluations
- JavaScript or TypeScript
- Python
- APIs
- SQL and relational databases
- Microsoft Azure
- Azure Functions
- Azure AI
- GitHub
- Cloud services

Software development experience is valuable, but we are not specifically looking for someone who has spent 10 years as a traditional developer. Someone who has spent the last few years aggressively teaching themselves how to build with AI may be more compelling to us than someone with significantly more conventional experience.

What you have actually built will carry significant weight.

- WHAT WE WILL CARE ABOUT IN THE INTERVIEW Expect us to be more interested in what you have explored and built than whether you can recite AI terminology.

We will want to understand:

- What AI tools and models you currently use
- What you have built with them
- What you experimented with recently
- Which developments in AI you think are genuinely important
- How you approach a technical problem you have never encountered before
- How you determine whether an AI system is actually reliable
- What you would automate if you joined Talos
- What you think AI will make possible over the next few years

If you have personal projects, prototypes, GitHub repositories, agents, automations, or strange experiments you built because you were curious, we want to see them.
- THE BOTTOM LINE This role is for someone who sees a new AI capability and immediately starts wondering what they could build with it.

You will experiment.

You will connect systems.

You will test ideas that fail.

You will build AI.

And occasionally, you will find something that fundamentally changes how part of the company operates.

Those are the opportunities we want you looking for.

We are not looking for someone who simply knows how to use ChatGPT.

We are looking for someone who is intensely curious about what AI can do, technically capable enough to explore it, and resourceful enough to turn that curiosity into working systems.

- ABOUT US Talos exists to strengthen the people and systems that shape a country.

Talos is a Canadian company headquartered in Victoria, BC, serving government clients across training, technology, talent, and public sector operations, primarily operating in Eastern Time Zone because of the clients in Ottawa and Gatineau, ON.

Our team is ambitious, energetic, and comfortable solving problems without waiting for someone else to provide the answer.

We work with the public sector across:

- Virtual training
- IT hardware and software
- Recruitment and headhunting
- Public sector operations support
- Technology and workflow improvement

From building secure technology systems to providing specialized staffing and running nationwide virtual learning programs, Talos designs reliable, human centered systems that help keep public sector operations strong and adaptable. The belief behind Talos is simple: stronger public servants create stronger institutions, and stronger institutions shape a stronger country.
- Pay: $30.00-$65.00 per hour Expected hours: 40.0 per week

Benefits

- Company events
- Dental care
- Discounted or free food
- Extended health care
- On-site parking
- Vision care

Application question(s):
- Tell us about the most interesting thing you have built with AI that nobody asked you to build. What did it do, how did you build it, and what did you learn?
- What is something unique about AI that most businesses might not know about, but should?
- Are you confident you can lead our AI integration and development?
- What is 1 thing that makes you unique?
- What is your preferred $ hourly rate or annual salary?

Work Location: In person

📌 AI Builder (Victoria)
🏢 TrueTraining / Talos
📍 Victoria