About the Role
Job Description:
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.Requirements:
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.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.