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Workstream is building an all-in-one HR, payroll, and hiring platform for the hourly workforce. The company serves leading brands including Burger King, Carl's Jr./Hardee's, IHOP, KFC, and Culvers, and is a Series B high-growth company backed by Founders Fund, BOND, and Coatue.
This is a founding engineer opportunity on Workstream's new AI-Native Services (AINS) team. You will be the first engineer on this initiative, responsible for building it from zero to one. You will shape the architecture, set the engineering bar, and help build the team that follows. This is a Staff-level role with direct access to leadership and real influence over how AINS grows. You will own the technical components—whether they work, how they fail, and how fast bespoke work becomes reusable. Pricing, deal acceptance, and margin models sit with the Head of Delivery and Head of GTM.
Key responsibilities include:
- Build and operate production AI agents and agentic workflows, including orchestration, tool use, data connections, deterministic logic, state management, and permissions.
- Work forward-deployed with design customers, sitting in their workflow, mapping messy reality, and building against live data.
- Build the evaluation harness: create eval datasets from real customer work, define pre-launch thresholds, build regression suites, and implement post-launch monitoring.
- Build the human-review layer: design exception queues, review tooling, escalation paths, and tracing that makes every agent decision auditable.
- Run shadow-mode parallel runs against the customer's existing process or provider and drive discrepancies to zero before go-live.
- Turn customer-specific work into reusable agents, integrations, and playbooks—productization is the default, customization the exception.
- Handle production incidents end to end and feed every failure back into evals and controls to prevent recurrence.
- Help set the technical bar as the team grows.
This is a full-time, remote position with occasional in-office visits as needed to support close cross-functional collaboration and key team initiatives.
REQUIREMENTS:
- You have personally built and operated at least one AI agent or agentic workflow in production. You can clearly explain how it worked, where it failed, how you evaluated it, and what you kept deterministic or human-led.
- Strong engineering judgment across models, orchestration, APIs, data and integrations, permissions, observability, and evaluations.
- You have worked directly with customers or end users—discovery, implementation, or incident resolution—and communicate clearly with non-technical people.
- You can break a messy workflow into deterministic steps, agentic decisions, human judgment, and exception paths—and define how each part will be tested.
- You care about keeping plausible but wrong AI output away from customers: grounded context, constrained actions, verification, evals, review, monitoring.
- You thrive in zero-to-one ambiguity: shipping weekly, owning outcomes, and doing whatever the service needs—including unglamorous review tooling and data plumbing.
- Exposure to a regulated domain (payroll, payments, tax, benefits, labor compliance) is a plus, not a requirement.
- Demonstrated production experience matters more than title or years.
