Staff Software Development Engineer - Applied AI

Wagepoint

$180K — $200K *
Enterprise Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 7+ years of software engineering experience, with expertise in building production systems.
  • 1.5+ years of experience with LLM-based or agentic systems in production environments.
  • Demonstrated ownership of end-to-end services, including both application and infrastructure code.
  • Proficient in Python; familiarity with .NET/C# is a plus.
  • Experience with cloud-native architectures, preferably Azure, and event-driven design.
  • Knowledge of security compliance for AI systems, including prompt injection mitigation.
  • Strong communication skills to translate technical intricacies into business outcomes.

Responsibilities

  • Own AI-powered services from architecture selection to production operation.
  • Design data-representation layers to support accurate LLM integration.
  • Establish automated evaluation pipelines for release management.
  • Implement security guardrails against vulnerabilities in AI services.
  • Manage Terraform, CI/CD, observability, and cost efficiency of owned services.
  • Integrate AI services with Wagepoint’s products and secure APIs.
  • Direct and review agentic development to uphold quality compliance standards.

Benefits

  • Opportunity to make a significant impact on Wagepoint’s growth.
  • Supportive team culture that values collaboration and celebrates successes.
  • Commitment to professional development and career growth.
  • Encouragement for innovation and experimentation in problem-solving.
  • Fully remote work option for flexibility and autonomy.
Full Job Description
The Role:

We're looking for a talented Staff Software Development Engineer - Applied AI who enjoys tackling hard problems and wants to create meaningful impact for small businesses across Canada. You'll own AI-powered services at Wagepoint end to end, from agent architecture through production operation. This role is defined by deep, hands-on ownership of one or more AI services, applying current agentic AI technologies to solve real payroll problems for our customers accurately, securely, and at scale. You will report directly to our VP, Engineering.

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.

You'll make sound local architecture calls without needing them ratified by committee. You select agent architectures for cost and predictability, design data representations that ground LLMs in accurate business context, and own the full path to production, including application code, infrastructure as code, CI/CD, evaluation, and observability. You build within Wagepoint's established AI platform standards (platform boundaries, persistence standards, guardrail rules) rather than authoring them, and you'll be the engineer others pull in when something in your domain breaks or needs deep expertise.

75% of your time goes to customer-facing AI products. The rest goes to Wagepoint's internal use of AI and our software factory, the agentic tooling and practices engineering runs on.

Wagepoint's goal is Level 4 on our agentic development ladder (you approve the spec, agents implement and review, you approve the PR), advancing toward Level 5 over time, without ever compromising quality in our highly regulated payroll and tax reporting environment.

Your output is measured by the reliability, cost efficiency, and correctness of what you ship.

What You'll Be Expected To Own:
  • Own one or more AI-powered services end to end, from agent architecture selection through production operation.
  • Build data-representation layers that ground LLMs in accurate, token-efficient business context.
  • Build automated eval pipelines that gate releases, and monitor drift and regressions in production.
  • Implement guardrails against prompt injection, tool misuse, and data exposure in owned services.
  • Own Terraform, CI/CD, observability, and cost engineering for owned services.
  • Connect AI services to Wagepoint's products and APIs via MCP and secure APIs.
  • Direct and review agentic development end to end for owned services, moving them toward Level 4 of the agentic development ladder without lowering the quality or compliance bar.

What You Bring To The Table:
  • 7+ years of professional software engineering experience, with a proven ability to design, build, and deploy production-grade systems.
  • 1.5+ years building and operating LLM-based or agentic systems in production SaaS or enterprise applications.
  • Track record of end-to-end service ownership, including application code, infrastructure as code (Terraform), CI/CD, observability, and production support.
  • Fluency in the current agentic toolchain, including stateful agent orchestration (LangGraph or equivalent), MCP for tool and data integration, and eval/observability platforms (Arize Phoenix, LangSmith, Langfuse, Braintrust, or similar).
  • Experience designing RAG and retrieval systems on vector-enabled data stores (PostgreSQL/pgvector or dedicated vector databases), and justifying the choice with cost and architecture tradeoffs.
  • Experience with model selection and routing across frontier and smaller models. A considered point of view on where a fine-tuned small language model would beat a frontier API call at Wagepoint is a plus, not a requirement.
  • High degree of agency. Comfortable optimizing API performance under real production constraints and building net-new systems from scratch where no established pattern exists yet.
  • Proficiency in Python with strong engineering fundamentals, and working knowledge of DDD and Clean Architecture principles applied to build highly performant, well-architected systems (prior DDD project experience not required). .NET/C# experience is a plus, not a requirement.
  • Experience with cloud-native architectures (Azure preferred), including Functions, AKS, and event-driven design.
  • Experience with security and compliance in AI systems, including prompt injection mitigation, data handling, least-privilege access, and guardrail design (OWASP LLM Top 10 or equivalent).
  • Strong communication skills, capable of translating technical AI tradeoffs into business outcomes.
  • 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.

Ready to join the team? Apply now and help us continue making payroll the easiest part of running a business.

Next steps:

If this sounds like the right fit, we'd love to hear from you! No need for a formal cover letter, just send us your resume and if you'd like, a few lines about what excites you about the opportunity.

If we agree it's a great match, someone from our team will reach out to schedule a call.

Department Engineering Locations Canada - REMOTE Remote status Fully Remote Yearly salary CAD180,000 - CAD200,000 Employment type Full-time

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