SOFTWARE ENGINEER / AI GROWTH BUILDER

Full Time | Victoria, BC

We are looking for a Software Engineer / AI Growth Builder who wants to explore what is becoming possible with AI and turn the strongest opportunities into working software, better operations, stronger services, and new business.

- Your primary job is to build. Your broader mandate is to help determine what is worth building and where technology can create meaningful business value.

Most of your time will be spent building, testing, integrating, and improving software. We are adding the AI Growth Builder mandate because we want someone who also thinks beyond assigned requirements.

You will work closely with leadership and our software team to identify problems worth solving, rapidly test new capabilities, build prototypes, connect systems and data, and turn the strongest ideas into reliable applications.

We move quickly, give people significant ownership, and expect them to operate effectively when the answer is not already known.

If you want a highly structured role where requirements are fully defined before they reach you, this will probably not be the right environment.

If you want significant freedom to explore, build, experiment, and influence where the company goes next, keep reading.

- WHY THIS ROLE IS DIFFERENT Most software engineering roles start with an established product, roadmap, or backlog.

This role often starts earlier.

What has recently become possible that Talos should be using?

You might

- Build an AI agent that takes ownership of a meaningful part of an operational process
- Connect models with company systems, documents, databases, APIs, and internal applications
- Rapidly determine whether a new AI capability can solve a problem that was impractical only months ago

You will have real operations, real users, company data, internal software, and an existing development team to work with. Initially, much of your work will involve our training division, TrueTraining.ca, where we operate large scale training programs and the software and processes that support them.

Over time, your work can expand across Talos operations in training, technology, staffing, business development, and public sector services.

- WHAT YOU WILL OWNBUILD SOFTWARE This is the core of the role.

You will

- Build applications, internal tools, AI agents, automations, and new capabilities within existing software
- Integrate APIs, databases, cloud services, company data, documents, and AI models
- Debug, test, evaluate, and improve systems until they are genuinely useful and dependable
- Turn successful experiments into secure, maintainable software that employees or clients can rely on

FIGURE OUT WHAT IS WORTH BUILDING We do not want every idea turned into a project.

Part of your job is determining which opportunities actually deserve engineering effort.

That means

- Rapidly prototyping ideas before significant time is invested
- Testing recent models, agents, coding systems, frameworks, and emerging AI capabilities against real problems
- Recognizing when an exciting technology is not actually practical and moving on quickly

CREATE BUSINESS VALUE We are not looking for someone who only waits for internal technical requirements.

You should develop enough understanding of our operations, clients, and services to recognize where technology could create value.

That could mean

- Identifying client or operational problems that Talos could solve with software, automation, or AI
- Building prototypes, demonstrations, or pilots around promising opportunities
- Recognizing when something we build internally could strengthen an existing service or become an entirely new offering

You do not need to be a salesperson.



You do need an instinct for business value.

Sometimes that means eliminating hundreds of hours of manual work.

Sometimes it means making an existing service substantially better.

Sometimes it means helping Talos win a new client, pilot, contract, or line of business.

- HOW WE WORKBUILD FAST. DEPLOY CAREFULLY. We expect aggressive experimentation.

Many ideas should be tested quickly. Some will work. Some will fail. Some should be abandoned within hours because the evidence says they are not useful.

That is a good outcome.

We do not want to spend months engineering something before determining whether anyone needs it.

Once something proves valuable enough to enter real operations or be put in front of a client, the standard changes.

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

A prototype proves an idea.

A production system has to survive reality.

You need to be capable of both.

SYSTEM OWNERSHIP MATTERS

Building the feature is not the end of the problem.

Strong engineers think about what surrounds it.

That includes understanding

- Where the inputs come from and whether they can be trusted
- Dependencies, exceptions, edge cases, and what happens when something fails
- How the system affects downstream employees, clients, processes, and other technology
- What monitoring, documentation, controls, and human review are needed once people depend on it

We want someone who can eventually own a system, not just complete individual development tasks.
- WHAT SUCCESS LOOKS LIKE

You are succeeding when

- Strong ideas move quickly from an opportunity or problem to something testable
- Useful prototypes become dependable systems that employees or clients actually use
- Your work creates measurable operational improvement, stronger services, or meaningful new business opportunities

Leadership should be able to bring you an unfamiliar problem and expect you to investigate whether technology can meaningfully solve it. Just as importantly, you should regularly bring forward opportunities that nobody asked you to investigate.
- WHO WE ARE LOOKING FOR The strongest candidates will combine software engineering ability with unusually high curiosity about AI and an instinct for where technology creates value. You are likely to do well here if you:
- Regularly experiment with new models, agents, APIs, coding tools, frameworks, and AI capabilities
- Can move from an idea to working software without needing every step defined for you
- Learn unfamiliar technical concepts independently and are comfortable opening documentation and figuring things out
- Can distinguish an impressive demonstration from something genuinely useful, reliable, and worth continuing
- Take ownership beyond your immediate code and think about how the complete system needs to work

We are particularly interested in things you built because you were curious, not because an employer assigned them to you.

- THE TECHNICAL BAR Using ChatGPT heavily is not enough.

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

Depending on your background, that could include experience with:

- Python, JavaScript or TypeScript, APIs, authentication, webhooks, web applications, and software integrations
- SQL,



relational data, cloud infrastructure, Git, debugging, testing, and modern software development practices
- LLM APIs, structured outputs, tool calling, agents, retrieval, evaluations, and AI enabled workflows

Our current environment includes technologies such as Microsoft Azure, Azure Functions, Microsoft Graph, APIs, relational data, Airtable, Microsoft 365, and AI model APIs. We are also actively exploring newer infrastructure such as Model Context Protocol, agent systems, and rapidly evolving AI development tools.

You do not need experience with everything listed here.

We care more about whether you can understand unfamiliar technology, build with it, and get to a working result.

- EXPERIENCE LEVEL We are deliberately open on experience level.

A highly capable person early in their career may be a better fit than someone with significantly more conventional software engineering experience.

A more experienced engineer may take ownership of larger systems and technical decisions much sooner.

The scope, seniority, responsibilities, and reporting relationship can reflect the level at which you are ready to operate.

What you have actually built and how you think will carry significant weight.

- WHAT WE WANT TO SEE Expect us to care more about evidence than AI terminology.

We want to understand

- What you have actually built or experimented with
- How you approach a technical problem you have never encountered before
- How you determine whether an AI system actually works and is reliable enough to use

If you have personal projects, GitHub repositories, agents, automations, applications, prototypes, or strange experiments you created simply because you wanted to know whether something was possible, we want to see them.
- ABOUT TALOS Our goal is to strengthen the people and systems that shape a country. Talos is a Canadian company headquartered in Victoria, BC. We build and operate services that strengthen the people and systems behind Canadian public sector organizations.

Our work includes

- Training and learning services
- Technology, workflow improvement, and IT services
- Recruitment, talent, and public sector operational support

Our training division, TrueTraining, delivers large scale virtual learning programs and operates internal software supporting scheduling, learners, instructors, assessments, communications, administration, and program delivery. Our team is unique, ambitious, and energetic. People here solve problems quickly, take ownership, and care about building something meaningful. That is why this role exists.

We are looking for someone who sees a new capability and starts asking:

- What can we build with this?
- Does it actually work?
- And if it does, how can it create meaningful value?

Pay: $63,000.00-$154,000.00 per year

Benefits

- Casual dress
- Company events
- Dental care
- On-site parking

Application question(s):
- 1. Tell us about something you built with AI that nobody asked you to build. What made you want to build it, what did you actually build, and what happened when you tested it?

- 1. Pick one software or automation system you have personally built. What is one failure, edge case, or ugly technical problem you discovered only after you started building it, and how did you deal with it?

- 1. You have two ideas. Idea A could save the company 20 hours per week and is technically straightforward. Idea B could potentially become a new client service but you are not yet sure it will work. You have one week. What do you do?

- 1. What is your preferred $ hourly rate or annual salary?

- 1. This position is IN-PERSON in Victoria BC. Do you understand?

Work Location: In person

📌 Software Engineer / AI growth builder (Victoria)
🏢 TrueTraining / Talos
📍 Victoria