Founding AI Engineer

About CodaAt Coda, we are building the next generation of AI-native solutions that allows mobility assets, like passenger cars and heavy-duty trucks, to be able to self-diagnose and predict mechanical issues. Our proprietary edge architecture allows us to process over 1,500+ raw vehicle signals in real-time, enabling AI-native reasoning that transforms standard telematics into actionable, predictive insights to prevent mechanical failures before they impact a fleet's operations.We operate with high autonomy, rapid iteration cycles, and a bias toward execution. We don't build in a vacuum—but we take complete ownership of everything we build from prototype to production.About the RoleAs our Founding AI Engineer, you will work directly alongside the CEO and the rest of the founding team to define how people interact with intelligent physical assets. Your goal is to build a radically simpler interface between humans and complex machines, making sophisticated machine intelligence accessible without requiring users to understand underlying data, protocols, models, or software infrastructure.Sitting at the intersection of AI, data science, data engineering, and product design, you will take primary responsibility for turning raw machine data into intuitive user experiences, architecting agentic workflows, building reliable agent harnesses, and shipping production-grade AI systems into the real world.What You'll DoDefine Human-Machine Interactions: Design intuitive AI interaction models based on driver, technician, and fleet workflows; translate user intent into sophisticated agentic workflows and prototype interactions rapidly with real users.Build Agent Intelligence & Tooling: Develop multi-step agentic workflows and agent skills for live and historical time-series data, enabling agents to select and invoke analytical tools via structured interfaces like Model Context Protocol (MCP).Applied Data Science & Analytics: Build analytical capabilities across statistical analysis, signal processing, anomaly detection, trend analysis, event detection, and model inference to process raw vehicle signals.Engineer the Agent Harness: Design reliable, observable, and testable agent harnesses managing context, memory, state, permissions, and guardrails, complete with automated evaluations for agent reasoning and tool selection.Data Pipeline & Infrastructure Integration: Build data pipelines that transform high-frequency machine data into agent-friendly formats, collaborating with Coda's backend team to connect agent workflows to cloud services.Drive Ownership in Ambiguity: Own critical, cross-disciplinary technical challenges end-to-end, moving seamlessly from understanding a user's workflow to shipping agentic software into production without pre-written specifications.Who You AreData & AI Engineering Fundamentals: You possess strong Python skills alongside practical experience with streaming or high-frequency time-series data engineering and backend infrastructure integration.Applied Data Science & ML Expertise: You have hands-on experience applying statistical analysis, signal processing, anomaly detection, and model inference to complex datasets.Production Agentic AI Builder: You have direct experience building production-grade agentic systems, including tool calling, multi-step workflows, context engineering, and structured interfaces like MCP.Harness & Reliability: You understand how to build robust evaluation pipelines, tracing, observability, context optimization, and safety guardrails around non-deterministic AI models.Strong Product Instincts: You hold deep empathy for non-technical users, able to dissect complex technical data and synthesize it into simple, trustworthy human experiences.How to ApplySend a short note to careers@coda-engine.ai with the following:Your resumeA brief description of the most complex AI/data problem or agentic workflow you’ve built and shipped into production.A link to your GitHub, personal project portfolio, paper, or demo of an intelligent system you’ve created.