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Croesus

Technical Lead, Innovation

Montreal, QC, Canada

Job type: Full-time
Apply by: Oct 24, 2026
Posting language: English
Posted: Sep 24, 2026

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Original job description

Company Description

Croesus provides innovative, high-performance, and secure wealth management solutions that include portfolio management systems, portfolio rebalancing tools, and application programming interfaces (APIs). These solutions empower wealth management professionals to improve their productivity, enhance their client relationships, make informed decisions, and maximize the management of their assets under management.

Croesus’s mission is to provide a superior experience to its clients, users, partners, and employees and to positively impact the community. With more than 200 employees in its Montréal, Toronto, and Geneva offices, Croesus has won several industry awards for being a high-quality solution provider and an outstanding employer.

Position

Croesus is building the next generation of wealth management software the way a startup would: small teams, short loops, real ownership, with the trust and reach of the incumbent behind us. The Innovation team is where the company experiments. We take the hardest, least-defined bets, prototype them, and put them in front of real customers to find out what's real. Some of those bets are AI-native. A lot of them aren't; platform work like core next-generation features live here too. What's constant is that we're operating before there's a defined product, a defined customer, or a defined metric, and we're comfortable there.

Most of what we build we validate and hand off, or kill with learnings attached. But when we see a real opportunity and no one else has the capacity to take it, we'll take it further ourselves. That's part of what makes this a place where your work has teeth.

We need the leader who makes a small team punch far above its size. Not someone who runs a process, but someone who sets the technical bar by being the best engineer in the room, and who is genuinely obsessed with how good software gets built.

This is not an engineering-manager role. We're not hiring you to run standups and shepherd tickets. You'll lead a small group of developers and researchers and be the person they bring the hard problem to: the one who goes deep when it counts and raises everyone's ceiling the rest of the time.

If you look at a slow, handoff-heavy way of building software and can't stop yourself from redesigning it in your head, keep reading.

What you'll actually do

Set the technical bar, and go deep where it counts (approx half your time). You're the technical center of gravity for the team. You own the architecture of what we build, across AI-native products and conventional platform work alike, and you make the hard build-vs-buy and design calls. Most days that's guiding: reviewing designs, unblocking people, being the expert with the answer. On the hardest problems, it's you collaborating in the code. You lead by raising the ceiling, not by writing every line.

Reinvent how the Innovation team builds: the AI-powered SDLC (approx a third of your time). This one is about our own build loop, not the company's platform. Your job is to make the Innovation team ship dramatically faster at the same quality by pushing AI and automation through how we work day to day: spec, CI/CD, testing, observability, tooling. Claude Code is our primary build environment today, though we're not precious about any one tool. If something ships faster, we use it. You'll define what agentic development actually means in practice within the team and strip out the manual steps and dependencies that slow us down. When something proves out, you share the pattern to the DevEx team who scale it across Croesus; you're the one discovering the better way of building, not the one running the company-wide rollout. This is about how we build, so it applies to everything we do, AI product or not.

Lead the people, and make the work count (the rest of your time). You directly lead our innovation developers and researchers: their growth, their focus, their delivery. Real one-on-ones, honest feedback, blockers cleared, focus protected, a team strong builders don't want to leave. With research specifically, your job is to push the work past interesting: framing it so experiments actually reach real customers and teach us something. Research that stops at findings hasn't finished the job here. You handle the manager basics without letting them crowd out the engineering, because the engineering is why you're here.

Requirements

What you'll bring

Deep, current engineering expertise. You've architected and shipped non-trivial systems, and you can still go all the way down into the code when the problem earns it.
Comfort across our stack, not just one corner of it: C# / .NET (.NET Core, REST/WebAPI) on the backend, TypeScript with Angular (our standard) and React (common on the Innovation side) on the frontend, and Python for the AI/ML work (RAG, agentic workflows, LangGraph, MCP-based tool integration). Nobody has all of it on day one, so go deep in most and ramp fast on the rest.
Range across real architectures (microservices, modular monoliths, CQRS, event-driven, clean REST/OpenAPI APIs), and the judgment to pick the one the problem actually needs, not the one that's fashionable.
You are AI-native in how you think and build. LLMs, agent frameworks, AI coding tools, evals: these are part of how you work, not a track you context-switch into. You have real intuition for what current models are good and bad at, and you use it before anything gets built. This holds whether the product you're building is "an AI product" or not.
A genuine point of view on the development lifecycle itself (CI/CD, testing, observability, developer tooling) and on how AI is rewriting it. You've made a team faster before, or you're itching to.
Enough leadership to grow a small team well, and the judgment to point sharp people at the bets worth making. People have done their best work near you.
You move fast in ambiguity. You frame the problem, make the call with what you have, and iterate. If you need a fully-scoped ticket to start, this isn't your role.
Comfortable working in a bilingual (French/English) environment.

We care more about what you've built and how you think than about titles or tenure. Think the systems that would hold up outside a demo.

What Success Looks Like

First 90 days. You know the team, the codebase, and where the real bottlenecks are. You've already made at least one concrete improvement to how we build (a slow loop removed, a tool introduced, a workflow rethought), and you've become the person the team routes its hardest technical calls to.

First 6 to 12 months. The team ships noticeably faster with no drop in quality, and the technical bar on what we put in front of customers is visibly higher. Several bets have been validated with real users. Where it made sense, and where we chose to, at least one has been taken further toward the product. The research work is landing with customers, not sitting in a findings doc.

How We Work

Small teams, real ownership, short loops. We decide with the information we have and we move. AI is part of the toolkit; we use it to go faster and think sharper, not to replace judgment. And we build in a regulated industry, so security and reliability are part of the craft here, not a gate someone else owns at the end. Your calls matter, and you'll see them in front of customers fast.

Why join Croesus ?

À la carte vacations
Annual salary + Corporate profit-sharing plan
Hybrid work, 2 days a week in office (Laval & Montreal offices)
Sports program
Gym available at our Laval head office
Telemedicine + group insurance (super useful for the family 😉 )
Group RRSP
Proximity to Montmorency & Mcgill metro
Ongoing training and development plan
Referral bonus
Indoor and outdoor parking & electric car recharging
Croesus boutique
Beautifully renovated and spacious office
Complimentary breakfast every morning
2X per month, Happy hours, prepared by our Croesus Life Partner

Are you interested in this challenge? Do you believe you have the qualities and expertise required for this position? Please complete your application today.

Although all applications are carefully analyzed, we will communicate only with those selected. Thank you for your interest in Croesus.

Are you interested in this challenge? Do you believe you have the qualities and expertise required for this position? Please complete your application today.

Although all applications are carefully analyzed, we will communicate only with those selected. Thank you for your interest in Croesus.

Apply About employer

More about this job

Responsibilities

Lead the Innovation team’s technical direction, architecture, and engineering quality across AI-native products and conventional platform work, while contributing directly to difficult technical problems. Improve the team’s development lifecycle through AI and automation, lead developers and researchers, and ensure experiments are validated with real customers.

Requirements

The role requires deep, current engineering expertise across backend, frontend, and AI/ML technologies, along with sound architectural judgment and practical experience using AI tools and frameworks. Candidates should be able to lead and develop a small team, improve software delivery practices, work effectively in ambiguity, and operate in a bilingual French- and English-speaking environment.

Skills

Technical Leadership
Software Architecture
C#
.NET
TypeScript
Angular
React
Python
Artificial Intelligence
Machine Learning
Large Language Models
Agentic Workflows
CI/CD
Testing
Observability
Team Leadership

Benefits

Flexible Vacation
Corporate Profit-Sharing Plan
Hybrid Work
Sports Program
On-Site Gym
Telemedicine
Group Insurance
Group RRSP
Ongoing Training And Development
Referral Bonus
Indoor And Outdoor Parking
Electric Vehicle Charging
Complimentary Breakfast
Employee Social Events

Visa sponsorship

Not detected in the job text

Keywords

Wealth Management
Innovation
Software Architecture
C#
.NET Core
REST
Web API
TypeScript
Angular
React
Python
Artificial Intelligence
Machine Learning
Large Language Models
Retrieval-Augmented Generation
Agentic Workflows
LangGraph
Model Context Protocol
Microservices
Modular Monolith
CQRS
Event-Driven Architecture
OpenAPI
Claude Code
CI/CD
Automated Testing
Observability
Developer Experience
Security
Regulated Industry

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