The Embodied AI Solutions Engineer is a hybrid technical role that sits at the intersection of solutions architecture, software engineering, delivery management, product thinking, and business consulting. Rather than fitting neatly into any single function, this role serves as the primary bridge between GenRobot's AI platform and the customer's real-world operations — owning the full journey from initial business discovery through technical design, hands‑on implementation, and measurable outcome delivery. Working closely with the GTM team, this role translates ambiguous customer needs into executable engineering solutions, embeds deeply within customer organizations to drive adoption, and is ultimately accountable for the business results that deployment creates — not just the technology that enables them.
Responsibilities
Customer Business Discovery
- Embed within customer organizations to map business workflows, data structures, and permission frameworks
- Identify high-impact processes where AI can drive meaningful transformation, and pinpoint core pain points
- Translate ambiguous business requests (e.g., "use AI to improve efficiency") into well‑scoped, actionable engineering problems
Solution Design & Technical Delivery
- Design and implement use‑case‑specific solutions leveraging RAG, AI Agents, and Prompt Engineering
- Break down data silos within customer environments by building data pipelines and ETL workflows
- Own model deployment, adaptation, fine‑tuning, and production stability
- Develop customized workflows and integration solutions that connect GenRobot's platform with customers' existing systems
End-to-End Project Management
- Lead the full delivery lifecycle including POC validation, on‑site implementation, and formal acceptance
- Train customer teams on AI systems and provide ongoing technical support
- Troubleshoot and resolve production issues in real time to ensure system reliability
- Gather structured customer feedback and channel insights back to the product team to drive platform improvements
Business Value Delivery
- Take ownership of measurable business outcomes — including cost reduction, efficiency gains, and quality improvements
- Quantify the ROI of AI deployments and deliver data‑driven impact reports to stakeholders
- Establish monitoring and operational frameworks that ensure sustained, long‑term value from AI adoption
Qualifications
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Robotics, or a related field; published research is a plus
- Embedded in the embodied AI / robotics ecosystem — you know the landscape, the players, and the technical challenges
- Hands‑on experience with LLM/AI systems including RAG, AI Agents, and Prompt Engineering; comfortable going deep on model‑level problem solving
- Proven track record delivering end‑to‑end AI or robotics projects in production
- Strong cross‑functional communicator; able to engage both technical teams and non‑technical business stakeholders
- High ownership mindset: comfortable being accountable for business outcomes, not just technical deliverables