AI developer building machine - learning models and image datasets for GenAIz's life science and pharmaceutical software. Collaborating with developers, designers, product, business, and architecture teams.
About the role
- Principal Software Development Engineer leading AI technical strategy and architecture for Wagepoint. Collaborating across teams and defining standards in a remote-first fintech environment.
Responsibilities
- 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.
Requirements
- 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.
Benefits
- 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.
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