Forward Deployed Engineer
- Location Palo Alto, California, United States
- Posted 2026-09-04
Original posting ↗ You apply on the company site — we never collect applications.
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Skills
PythonSQLPrompt EngineeringAgents
Excerpt from the original posting
Forward Deployed Engineer About Arkham: Arkham is a Data & AI platform that helps large enterprises: - Unify fragmented systems and data - Build a single source of trusted operational metrics - Solve complex challenges with AI tailored to their operations Teams at Circle K and Kimberly-Clark partner with us to deploy AI-powered solutions for sell-out forecasting, pricing and promo analysis, and automated order assignment. With Arkham, they achieve high-impact results fast, creating a strong foundation for long-term AI transformation. About the Role As a Forward Deployed Engineer , you help drive the AI transformation journey for our customers. You work hands-on across data science, AI architecture, and implementation, partnering closely with client stakeholders to deliver high-impact solutions. Once a customer's Data Platform is live in Arkham, you help deliver and expand AI use cases. You partner with BI, Finance, Operations, and business stakeholders to: - Identify high-leverage AI opportunities - Build robust ML and GenAI solutions - Deploy production-ready systems - Support adoption across the client organization You will typically contribute to 1-4 implementations simultaneously, working alongside senior team members. What You'll Work On - Build and deploy ML models (like forecasting, optimization, clustering, and anomaly detection models) - Develop Generative AI workflows - Implement AI Agents that automate analysis and operational decisions - Follow best practices for model monitoring, retraining, and governance - Contribute to the first "Aha" moment: within 2-4 weeks, help deliver an operational AI solution that solves a core business pain point - Define data requirements and modeling strategies in collaboration with the team What We Require - 2-3 years of hands-on Data Science experience - Experience delivering ML systems into production - Some exposure to client-facing or stakeholder-intensive environments - Solid proficiency in Python and SQL - Experience with forecasting and time-series models - Experience with supervised and unsupervised ML - Familiarity with Generative AI and prompt engineering - Familiarity with AI agents and LLM-based workflows - Proficiency with Git and collaborative development workflows - Good understanding of statistical modeling and model evaluation - Strong communication and collaboration skills Why This Role Is Different You don't just build models, you help drive transformation. You work directly wit…