Staff Applied AI Engineer

About the role

You'll own applied AI across Doss: Dossbot (query, analyze, and automate via chat), AI-assisted schema and workflow generation, and the agentic automations that turn back-office busywork into background processes. You'll be the technical anchor for how foundation models meet a transactional system of record.

What you’ll do

• Own the applied AI architecture end-to-end: model selection, orchestration, RAG over the unified operational data model, evals, guardrails, and cost/latency budgets in production.
• Build Dossbot into the primary interface for operations: natural-language search, analysis, and automation grounded in live supply-chain, finance, and ops data.
• Engineer AI-assisted tooling that uses foundation models to propose, validate, and apply customer schemas and workflow definitions on live production tenants.
• Design agentic workflows that act inside enterprise guardrails: permission-aware, auditable, tenant-isolated, and safe to run against a customer's system of record.
• Stand up the eval and observability infrastructure to measure quality, catch regressions, and proactively detect anomalous or risky emergent behavior.
• Partner with product, design, and our Forward Deployed team to deliver on their highest-leverage AI use cases.
• Mentor and shape engineering culture as the team's center of gravity for applied AI, raising the bar on how we build, evaluate, and ship LLM-powered systems.

What we’re looking for

• Experience Shipped LLM-powered features or agents to production and operated them at scale, not just prototypes or demos.
• Deep hands-on work with foundation model APIs, RAG pipelines, tool use/function calling, prompt and context engineering, and fine-tuning where it earns its keep.
• Built eval harnesses and guardrails for non-deterministic systems running against business-critical data.
• Strong backend fundamentals: Designing systems, Postgres, and cloud services for reliable, multi-tenant web applications.
• Going from 0 to 1 in ambiguous settings, and judgment for when AI is the right tool and when it isn't.

Qualities

• Team player: you bring positivity, openness, and curiosity to the team every day.
• Growth mindset: everything is an opportunity to learn and improve yourself, the team, and the company.
• Craftsmanship: you care about making something of quality.
• Customer First: you care immensely about the customer experience journey and want to create a product full of delight.
• Pragmatic: you make the right decision based on circumstance, not theory.
• Low Ego: you work best in collaborative environments where everyone supports the team.