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We are hiring a GenAI Engineer to join a team building and delivering real-world generative AI solutions - systems that move beyond prototypes and into production, where real users rely on them every day.
You'll take complex problems from the first customer conversation through to a working system running in their environment. You'll build GenAI solutions that are deployed, used, and relied upon - not just demos or experiments.
The problems are unusual, and the constraints are real: on-premise and air-gapped deployments, strict data handling requirements, and complex customer environments. A meaningful part of your work will happen on-site with the people who use the systems you build.
What you'll do:
Build end-to-end GenAI systems: RAG pipelines, agentic workflows, document understanding, and extraction from messy real-world data.
Own the full lifecycle - from data pipelines and model/prompt design to evaluation, deployment, monitoring, and the critical work of making systems reliable and production-ready.
Define what success looks like for each use case, measure performance, and stand behind the results.
Work directly with customers on-site, translating their needs into practical technical solutions.

We're looking for a Senior AI Solutions Builder to join our Product team. In this role, you will design, build, and ship AI-powered solutions that enhance productivity and drive measurable business value across the organization.

You will operate at the intersection of AI, data, pricing and business - owning the end-to-end development of agents, copilots, and workflow automations that directly inform decisions and eliminate manual work.

You are both a builder and an enabler. You ship solutions yourself and raise the AI capability floor for the teams around you. You'll collaborate closely with Product, Engineering, CS, Sales, and builders across the company to deliver outcomes that improve decision velocity, product and operational efficiency, and long-term growth.

You Will

Design and ship AI-powered copilots, agents, and decision-support tools for the Product team, starting with Pricing.

Build data pipelines and analytical models for pricing intelligence.

Develop autonomous agents that automate recurring Product tasks.

Automate manual workflows across product tools so the right action happens when a signal fires.

Build LLM-based scoring models that give roadmap and prioritization decisions a data backbone.

Enable and upskill product teams through AI playbooks, sessions, and hands-on co-building.

Collaborate with builders across Engineering, CS, GTM, and other teams to co-create solutions that scale.

Define and track impact: time-to-insight, decision velocity, manual hours eliminated, and business outcomes.