AI Native Forward Deployed Engineer

About the Role

This position is a critical hire for Tread as we scale from $XM to $XXM+ Annual Recurring Revenue (ARR). The role is designed to close the gap between our customers' complex, high-stakes operations and our AI-native SaaS platform. You will be the technical bridge, embedding directly into the field environments of haulers, producers, and contractors to observe real-time workflows and translate them into immediate software solutions. Success is defined by your ability to own the end-to-end technical relationship, turning field observations into deployed features within hours, not sprints. This is a full-time, remote position with potential travel for on-site implementation and customer visits.

What You'll Do

Your primary responsibility is to act as the technical advocate and implementation lead for assigned customer portfolios within the construction materials logistics ecosystem. You will spend significant time embedded in operational environments - such as dispatch centers, scale houses, and back-office suites - to witness workflows firsthand. During these visits, you will investigate and resolve critical technical issues on the same day they arise.

You will own the end-to-end technical delivery for new customer implementations. This includes designing and executing API integrations, performing complex data mapping, and configuring workflows to connect haulers, producers, and contractors to the Tread platform. You will build custom integrations, data pipelines, and automation to handle complex requirements, ensuring seamless connectivity for scale house operations and freight reconciliation.

A core function of this role is rapid prototyping and validation. You will translate raw field observations into prioritized product requirements and acceptance criteria, contributing directly to Tread's codebase (Rails API, GraphQL, React). You will build and iterate on customer-specific dashboards and reporting tools that provide real-time operational performance visibility. This feedback loop is essential; you will feed structured, prioritized insights back to Product and Engineering, enabling data-driven roadmap decisions.

You will also author detailed integration guides, API documentation, and self-serve onboarding materials to accelerate adoption and reduce future support friction. Facilitating quarterly business reviews (QBRs) is another key duty, where you will demonstrate value, uncover expansion opportunities, and align on future outcomes with strategic accounts. By partnering with design and product teams, you will help prototype and validate solutions directly with end users in their operational context.

Requirements

To succeed in this role, you must possess a Bachelor's degree in Computer Science, Engineering, or a related technical field. You are required to have 3+ years of professional software engineering experience with hands-on production systems. A proven track record of building and maintaining integrations with external APIs and data-intensive workflows is essential.

You must be proficient in server-side development, with strong skills in Ruby or Python, and comfortable working with JavaScript for front-end or Node-based tooling. Experience working with relational databases and writing efficient queries against large datasets in production environments is mandatory. You must understand core software development practices, including testing, version control, CI/CD, and observability in deployed systems.

The ideal candidate must be able to work independently, making sound technical decisions with incomplete information in dynamic, high-stakes environments. You must communicate clearly and effectively with both technical and non-technical stakeholders, adapting your language for drivers, operators, and executives. You need to be comfortable working fully remotely while maintaining strong collaboration with a distributed, asynchronous team. A passion for using technology to solve hard operational problems in the physical world is a core requirement.

Nice to Have

While not required, experience with logistics, supply chain, or transportation operations and associated data models is highly valuable. Familiarity with construction materials, including aggregates, asphalt, or concrete workflows, provides significant context. Background in high-throughput data ingestion and event-driven architectures is also advantageous. Experience contributing to open source projects or public codebases is a plus.