Principal Software Engineer - Applied Ai
Wagepoint
At Wagepoint, we're good people. It's easy to feel that way when you're surrounded by folks doing the best work of their careers, building great payroll software for small businesses across Canada.Our team brings together diverse backgrounds, perspectives, experiences, and ideas to make payroll the easiest part of running a business.We're remote-first, growing, and looking for passionate people who don't settle for the first solution or the way it's been done before. We care deeply about our customers and each other, and understand that when it comes to payroll, getting it right matters.Our values guide how we work and what we expect from one another:Cultivate Impact
by focusing on what matters most and delivering meaningful outcomes for our customers.Unify as One Team
by collaborating openly, communicating clearly, and rallying around shared goals.Stay Curious and Kind
by challenging assumptions, learning quickly, and leading with empathy.If you want to build the future of payroll in a place where your ideas are welcomed and your contributions matter, look no further!The Role:We’re looking for a talented
Principal Software Development Engineer - Applied AI, who enjoys tackling hard problems and wants to create meaningful impact for small businesses across Canada. You’ll set the technical strategy for AI Products at Wagepoint, authoring thearchitecture decision records that define platform boundaries, persistence standards, and quality gates for every team building AI features, and setting the guardrails that let Engineering teams experiment with agentic AI. You will report directly to our
VP, Engineering.Your decisions are the ones other engineers’ proposals must cite and align to. Other teams’ roadmaps depend on getting your calls right. You’ll keep Wagepoint’s AI platform choices current against a fast-moving landscape, articulate tradeoffs in terms leadership can act on, and multiply the org through mentorship, pairing with and unblocking the engineers building on your standards.Like every Principal Engineer at Wagepoint, you also carry broad architectural leadership beyond AI, including well-architected, highly performant distributed systems, and AI-augmented development practices across the SDLC.Like every engineer at Wagepoint, you do not write software by hand. You’re a major contributor to the software factory, the agentic pipeline of specs, agent implementation, agent review, and human approval that produces our software. You’ll own specific agents within it and work with your teammates to constantly improve the factory itself.Wagepoint’s goal is Level 4 on our agentic development ladder (engineers approve the spec, agents implement and review, engineers approve the PR), advancing toward Level 5 over time, without ever compromising quality in our highly regulated payroll and tax reporting environment. You are responsible for making that transition possible.85% of your focus is customer-facing AI products and the platform beneath them. The rest goes to building Wagepoint’s internal use of AI and our software factory.This role is measured by scope of influence, not just personal output.What You'll Be Expected To Own:Author the decision records that define how AI gets built org-wide, and resolve cross-team ambiguity with written, cited decisions.Define and maintain the boundary between AI services and the product stack, and own the shared service kit.Make quantified platform calls (evals, observability, persistence) against named vendors with cost models.Define how every AI team gates quality: eval standards in CI/CD, drift monitoring, release criteria.Set resource-isolation and agentic-workflow guardrails, and own the responsible AI and audit posture org-wide.Keep platform choices current against the landscape, and publish dated verification notes and revisit triggers.Lead design of large-scale, distributed, customer-facing systems where AI intersects the product stack, and apply DDD to define domain boundaries.Be a go-to technical resource across teams, unblock high-impact initiatives, and shape engineering-wide standards through RFCs and reviews.Set the org-wide path from today’s baseline to Level 4 of the agentic development ladder and beyond toward Level 5, while holding the quality and compliance bar required in payroll and tax reporting.What You Bring To The Table:10+ years of professional software engineering experience with progressively increasing impact, including multiple years designing and operating production LLM/agentic systems at Staff-level scope or above.Proven technical leadership designing distributed systems and microservices for complex domains, with working knowledge of DDD and Clean Architecture principles applied to build highly performant, well-architected systems (prior DDD project experience not required).Full-stack breadth, spanning modern front-end frameworks and a Python back-end, sufficient to lead architecture across the entire product stack, not just AI services. .NET/C# experience is a plus, not a requirement.Track record of authoring architecture standards adopted beyond your own team, producing decision records that other senior engineers review, cite, and build on.Demonstrated quantified build-vs-buy decisions against named vendors (e.G., eval/observability platforms, vector stores), with cost models and explicitly rejected alternatives.Deep fluency in the current AI platform landscape: stateful agent orchestration, MCP and inter-agent (A2A) interoperability, eval-gated CI/CD, and vector-enabled persistence (PostgreSQL/pgvector, DiskANN-class indexing, managed offerings).A considered point of view on where Wagepoint’s model strategy should be in two years, including whether and where to adopt fine-tuned small language models versus frontier APIs, grounded in cost, latency, and control tradeoffs.Experience defining platform boundaries between AI stacks and an existing product stack (e.G., Python AI services alongside .NET), including shared service-kit libraries other teams consume.Security and governance leadership: resource isolation, agentic workflow guardrails, responsible AI in a regulated, money-movement domain.Executive communication, articulating platform tradeoffs in terms leadership can act on, covering cost, risk, and optionality, not just engineering detail.A high degree of agency, building net-new systems and optimizing API performance where no established pattern exists, forging the path rather than waiting for one, with demonstrated ability to bring other engineers along that path.Demonstrated multiplier effect through mentorship: pairing with, unblocking, and growing senior engineers.A passionate and key contributor to Wagepoint’s software factory, directing and reviewing agentic development while maintaining and improving our high quality and compliance bar.What we bring to the table:Impact:
Dig in and directly contribute to Wagepoint’s growth and success.Culture:
Work alongside a team that genuinely enjoys solving problems together, celebrates wins, supports one another through challenges, and still finds time for the occasional terrible joke.Growth:
We believe learning is part of the job. We’re committed to helping you Get Better Every Day (a representation of our Stay Curious and Kind value!) by offering professional development, new experiences, and career growth as we continue to evolve.Innovation:
Curiosity and experimentation encouraged! Bring ideas, challenge assumptions, responsibly utilize AI, and help shape better ways of working.Remote:
Work from wherever you do your best work. Wagepoint has always been remote-first, giving you flexibility, autonomy, and hopefully a little extra time with the people (and pets) you love.In 2026, we were recognized as one of Canada's Best Workplaces for Mental Wellness and Inclusion. That commitment extends to our hiring process, where we strive to create an experience that is welcoming, respectful, and inclusive from day one.We welcome applicants from all backgrounds, experiences, identities, and perspectives, and we're committed to building a workplace where everyone can thrive.As a remote company, all interviews are conducted virtually. If you require accommodation at any stage of the recruitment process, please let us know. We're happy to support you!As part of our hiring process, AI-based tools are used to support the initial review of applications. Rest assured, our People Ops team carefully reviews all applications and makes the final decisions on candidate progression.
#J-18808-Ljbffr
by focusing on what matters most and delivering meaningful outcomes for our customers.Unify as One Team
by collaborating openly, communicating clearly, and rallying around shared goals.Stay Curious and Kind
by challenging assumptions, learning quickly, and leading with empathy.If you want to build the future of payroll in a place where your ideas are welcomed and your contributions matter, look no further!The Role:We’re looking for a talented
Principal Software Development Engineer - Applied AI, who enjoys tackling hard problems and wants to create meaningful impact for small businesses across Canada. You’ll set the technical strategy for AI Products at Wagepoint, authoring thearchitecture decision records that define platform boundaries, persistence standards, and quality gates for every team building AI features, and setting the guardrails that let Engineering teams experiment with agentic AI. You will report directly to our
VP, Engineering.Your decisions are the ones other engineers’ proposals must cite and align to. Other teams’ roadmaps depend on getting your calls right. You’ll keep Wagepoint’s AI platform choices current against a fast-moving landscape, articulate tradeoffs in terms leadership can act on, and multiply the org through mentorship, pairing with and unblocking the engineers building on your standards.Like every Principal Engineer at Wagepoint, you also carry broad architectural leadership beyond AI, including well-architected, highly performant distributed systems, and AI-augmented development practices across the SDLC.Like every engineer at Wagepoint, you do not write software by hand. You’re a major contributor to the software factory, the agentic pipeline of specs, agent implementation, agent review, and human approval that produces our software. You’ll own specific agents within it and work with your teammates to constantly improve the factory itself.Wagepoint’s goal is Level 4 on our agentic development ladder (engineers approve the spec, agents implement and review, engineers approve the PR), advancing toward Level 5 over time, without ever compromising quality in our highly regulated payroll and tax reporting environment. You are responsible for making that transition possible.85% of your focus is customer-facing AI products and the platform beneath them. The rest goes to building Wagepoint’s internal use of AI and our software factory.This role is measured by scope of influence, not just personal output.What You'll Be Expected To Own:Author the decision records that define how AI gets built org-wide, and resolve cross-team ambiguity with written, cited decisions.Define and maintain the boundary between AI services and the product stack, and own the shared service kit.Make quantified platform calls (evals, observability, persistence) against named vendors with cost models.Define how every AI team gates quality: eval standards in CI/CD, drift monitoring, release criteria.Set resource-isolation and agentic-workflow guardrails, and own the responsible AI and audit posture org-wide.Keep platform choices current against the landscape, and publish dated verification notes and revisit triggers.Lead design of large-scale, distributed, customer-facing systems where AI intersects the product stack, and apply DDD to define domain boundaries.Be a go-to technical resource across teams, unblock high-impact initiatives, and shape engineering-wide standards through RFCs and reviews.Set the org-wide path from today’s baseline to Level 4 of the agentic development ladder and beyond toward Level 5, while holding the quality and compliance bar required in payroll and tax reporting.What You Bring To The Table:10+ years of professional software engineering experience with progressively increasing impact, including multiple years designing and operating production LLM/agentic systems at Staff-level scope or above.Proven technical leadership designing distributed systems and microservices for complex domains, with working knowledge of DDD and Clean Architecture principles applied to build highly performant, well-architected systems (prior DDD project experience not required).Full-stack breadth, spanning modern front-end frameworks and a Python back-end, sufficient to lead architecture across the entire product stack, not just AI services. .NET/C# experience is a plus, not a requirement.Track record of authoring architecture standards adopted beyond your own team, producing decision records that other senior engineers review, cite, and build on.Demonstrated quantified build-vs-buy decisions against named vendors (e.G., eval/observability platforms, vector stores), with cost models and explicitly rejected alternatives.Deep fluency in the current AI platform landscape: stateful agent orchestration, MCP and inter-agent (A2A) interoperability, eval-gated CI/CD, and vector-enabled persistence (PostgreSQL/pgvector, DiskANN-class indexing, managed offerings).A considered point of view on where Wagepoint’s model strategy should be in two years, including whether and where to adopt fine-tuned small language models versus frontier APIs, grounded in cost, latency, and control tradeoffs.Experience defining platform boundaries between AI stacks and an existing product stack (e.G., Python AI services alongside .NET), including shared service-kit libraries other teams consume.Security and governance leadership: resource isolation, agentic workflow guardrails, responsible AI in a regulated, money-movement domain.Executive communication, articulating platform tradeoffs in terms leadership can act on, covering cost, risk, and optionality, not just engineering detail.A high degree of agency, building net-new systems and optimizing API performance where no established pattern exists, forging the path rather than waiting for one, with demonstrated ability to bring other engineers along that path.Demonstrated multiplier effect through mentorship: pairing with, unblocking, and growing senior engineers.A passionate and key contributor to Wagepoint’s software factory, directing and reviewing agentic development while maintaining and improving our high quality and compliance bar.What we bring to the table:Impact:
Dig in and directly contribute to Wagepoint’s growth and success.Culture:
Work alongside a team that genuinely enjoys solving problems together, celebrates wins, supports one another through challenges, and still finds time for the occasional terrible joke.Growth:
We believe learning is part of the job. We’re committed to helping you Get Better Every Day (a representation of our Stay Curious and Kind value!) by offering professional development, new experiences, and career growth as we continue to evolve.Innovation:
Curiosity and experimentation encouraged! Bring ideas, challenge assumptions, responsibly utilize AI, and help shape better ways of working.Remote:
Work from wherever you do your best work. Wagepoint has always been remote-first, giving you flexibility, autonomy, and hopefully a little extra time with the people (and pets) you love.In 2026, we were recognized as one of Canada's Best Workplaces for Mental Wellness and Inclusion. That commitment extends to our hiring process, where we strive to create an experience that is welcoming, respectful, and inclusive from day one.We welcome applicants from all backgrounds, experiences, identities, and perspectives, and we're committed to building a workplace where everyone can thrive.As a remote company, all interviews are conducted virtually. If you require accommodation at any stage of the recruitment process, please let us know. We're happy to support you!As part of our hiring process, AI-based tools are used to support the initial review of applications. Rest assured, our People Ops team carefully reviews all applications and makes the final decisions on candidate progression.
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