Forward Deployed Engineer (New York)
About the Company OneTrack connects systems of record with places of action. We deploy AI for the companies that run the physical economy. Our platform, OneTrack AiOn, connects business systems, operational data, and company knowledge so teams can build applications, answer complex questions, and automate work across their organization. Today, we partner with some of the largest companies in logistics and manufacturing, including clients like Church & Dwight, Ecolab, The Wonderful Company, CJ Logistics, Ryder, GXO, and many others. Some clients deploy AiOn using their existing software and data. Others combine it with OneTrack’s sensors and computer vision to connect what happens on the floor with what lives in their systems. About the Role We’re looking for a Forward Deployed Engineer to embed with clients and turn that capability into everyday practice. You’ll work alongside frontline teams, operations leaders, analysts, and IT to understand how their business runs, identify valuable problems, and build solutions that become part of how they operate. You’ll own the path from an ambiguous business problem to a working deployment: understanding the workflow, connecting the data, validating the logic, shipping the solution, and helping people use it successfully. Responsibilities Embed with client teams. Spend time on site and in their working routines. Learn how decisions get made, where work gets stuck, and which problems are worth solving first. Turn those findings into a deployment plan with clear owners and measurable outcomes. Connect and make sense of their data. Work with client IT and data owners to bring together ERP, warehouse and labor management systems, data warehouses, APIs, spreadsheets, and documents. Resolve inconsistent identifiers, unclear definitions, and data quality issues. Teach AiOn how the business works. Capture the client's terminology, processes, relationships, and operating rules as reusable knowledge and skills. Translate agreed calculations into tested procedures so teams get consistent, trustworthy results. Build applications and automations. Use AiOn’s tools and write code where needed to deliver dashboards, operational apps, recurring analyses, alerts, and agent workflows. Carry solutions through testing, rollout, troubleshooting, and ongoing refinement. Deploy with and without sensors. Deliver value from existing business data alone. When a use case benefits from physical visibility, partner with OneTrack’s hardware and field teams to incorporate sensor events, telemetry, and vision insights. Establish permissions and ownership. Work with clients to define who can access data, approve actions, maintain business context, and own each workflow. Validate that the deployment behaves correctly for different users and sites. Build client capability. Run working sessions, train internal champions, and build the first use cases alongside the people who will own them. Help clients develop the confidence and skills to build the next ones themselves. Improve the product through field experience. Bring clear problem statements, reproducible issues, and reusable solutions back to engineering and product. Help turn successful deployments into patterns that work across clients. Responsibilities - What you might work on Combine warehouse and labor data into a daily performance workflow that highlights exceptions and gives supervisors a consistent basis for action. Connect ERP and transportation data to reconcile freight spend and investigate discrepancies. Turn a spreadsheet process into a shared application with validated calculations, permissions, and scheduled updates. Combine sensor observations with operational records to support safety coaching, investigate damage, or understand lost capacity. Help an analytics team build its first AiOn applications, then establish the knowledge and ownership needed to expand across departments. Required Skills - What you bring 2 years of software engineering or technical deployment experience, including direct work with customers (e.g., onboarding, troubleshooting, or gathering requirements). Hands-on experience building and deploying agentic applications, including agents that plan and execute multi-step tasks, with working knowledge of prompt engineering, agent skills, and memory design and tuning. Strong Python and SQL skills, comfort working with APIs and data pipelines, and the ability to debug across unfamiliar systems. The ability to turn an open-ended business problem into a practical technical solution, explain the tradeoffs, and ship it. Strong client communication. You can work through a data issue with an engineer, understand a supervisor’s daily routine, and explain progress to an executive. Good judgment about data quality, access controls, testing, and reliability. You verify that calculations and AI outputs hold up against source data and actual business practice. Comfort building with AI tools and reviewing the code and outputs they produce. Ownership and persistence when requirements are incomplete, systems are messy, or adoption takes more work than expected. Willingness to travel and work alongside clients at their facilities. Preferred Skills - Helpful experience Logistics, warehousing, manufacturing, agriculture, transportation, or other physical operations. Enterprise implementations involving ERP, WMS, LMS, TMS, or business intelligence systems (PowerBI, Tableau, Looker, etc.) Building LLM applications, tool integrations, evaluations, or automated workflows. Frontend, backend, basic cloud infrastructure, or similar full-stack application development. IoT, computer vision, or operational telemetry. Training users and leading changes to established ways of working. Pay range and compensation package $100,000-$150,000 PTO, healthcare, performance-based compensation, and other benefits Frequent travel to clients across North America Responsibilities - What success looks like Clients use what you build in their daily work. They trust the numbers, understand the controls, and can point to improvements such as less manual reporting, faster investigations, fewer unresolved exceptions, or better use of operational capacity. Their internal champions can extend the deployment, and your field experience makes the next client implementation better. You’ll have direct ownership of meaningful client problems and a close connection to the engineers building the platform. The work will take you from a conversation on the warehouse floor to a data model, from a prototype to a production workflow, and from one successful use case to adoption across an organization.
