Dodge AI is building the enterprise automation platform for ERP. Every year, over $100B is spent on consultants to maintain legacy ERP systems. We are starting by helping enterprise IT/AMS (Application Managed Services) teams automate incident management and configuration across complex SAP landscapes, enabling them to reduce maintenance costs and improve system reliability at scale. This is our first wedge toward a broader vision of enterprise-wide, AI-powered ERP automation.
Today, our platform automates L1/L2 ERP support, helping reduce resolution times and consulting hours, while also auditing configs and accelerating service delivery.
We're Tier-1 VC-backed ($2.65M Pre-Seed; backed by Accel & Google Labs' AI Futures Fund), live with customers (Fortune 500s), and moving fast. If you're excited to build with real users, solve hard technical problems, and shape the future of ERP, we’d like to chat.
End-to-end ownership over ERP projects, designing RL environments, building platforms, and solving scalability challenges in a fast-paced, high-growth team.
As part of Dodge AI’s engineering team, you will have end-to-end ownership over projects that push the frontier of self-healing ERP systems. You will work on a mix of research engineering, which includes designing novel reinforcement learning (RL) environments, agentic systems, and evaluation harnesses, as well as platform engineering, which involves building human-in-the-loop platforms, scaling data infrastructure, and designing annotator workflows.
This role is not narrow. One week you might prototype a new RL environment from a research paper, the next you will be deploying distributed experiments on Kubernetes, and the week after you will be improving the reliability of our Next.js dashboards or building a Kafka pipeline for incident lifecycle analytics.