Product Engineer

The Role

The Product Engineer designs, builds, deploys, and supports technology for farmers, workers, and fishers in more than 50 countries. This is a full-stack role on the Applied Intelligence team. The people who use what you build are small producers and cooperative managers, not a persona in a deck.

You own the product lifecycle: discovery with users, development, deployment, monitoring, and continuous improvement. Requirements come out of field research and change monthly, and direct user feedback drives product decisions. You work alongside the Digital Technology team, which runs the organization’s core systems.

What You Would Build

• The producer agent. A trilingual agent (English, Spanish, French) that works by voice, image, and document, designed for people whose connection drops and whose device is shared. Year 1 reaches 350+ producers across ten cooperatives, toward a goal of 5.1 million beneficiaries.
• Impact evidence surfaces. Evidence on 1,030 Certificate Holders in 53 countries, presented so a producer, a cooperative manager, a brand partner, and a funder each get what they need from one shared data foundation.
• Audit platform. Built on Cloudflare Workers and D1 and running under real audit load.
• Reconciliation underneath all of it. Three source systems that disagree across roughly a thousand organizations, resolved without silently averaging. Showing the disagreement is the requirement, not a failure state.

What Makes This Role Different
Fair Trade USA's Digital Technology team operates the organization’s systems of record and sets its standards for security, integration, and data integrity. This role builds new producer-facing products within those standards, in partnership with that team.

• Built from scratch. Nobody sells a trilingual, voice-first agent for small producers on intermittent connectivity. You build it.
• Changing requirements. Requirements come out of field research and change monthly.
• Probabilistic systems. These systems degrade silently rather than failing a test, so you build evaluation, not only test suites.
• A learning loop. You will be wrong often, on purpose, because that is how the learning loop runs.

Key Responsibilities

Product Development & Engineering

• Design, develop, deploy, and maintain applications and services across the full stack, from React front ends to Workers, APIs, and databases.
• Build solutions for farmers, cooperatives, auditors, and business partners, starting from how they work today.
• Turn field research, user feedback, and evolving needs into production software, often from problems that are under-specified because no one has solved them before.
• Build systems that bring together structured and unstructured data from multiple sources.
• Make architecture and technical design decisions, and choose technology where no existing product fits, in coordination with Digital Technology.
• Review code with the Applied Intelligence team and hold a high standard for quality, performance, security, and maintainability.

AI, Data & Platform Solutions

• Build AI-enabled products using hosted LLM APIs and local inference nodes.
• Build interfaces and workflows for voice, image, and document input in English, Spanish, and French, for low-bandwidth and shared-device use.
• Build views that surface insights, evidence, and impact data for producers, cooperative managers, brand partners, and funders.
• Design and implement reconciliation, validation, and transparency across source systems that preserve and display disagreement instead of averaging it away.
• Build evaluation for probabilistic systems: define what good looks like, measure it continuously, and catch silent degradation before users do.
• Evaluate emerging technologies and recommend where they improve the product and the user experience.

Deployment, Operations & Continuous Improvement

• Own deployment, monitoring, troubleshooting, and operational support for your products. You do not hand off at the merge.
• Investigate production issues, identify root causes, and implement long-term fixes.
• Establish monitoring, evaluation, and quality assurance approaches for both traditional software and AI-powered applications.
• Improve reliability, performance, and usability through iterative releases.
• Contribute to technical documentation, implementation standards, and engineering practices.

User Engagement & Cross-Functional Collaboration

• Partner directly with users, cooperative managers, and subject matter experts to understand workflows and what actually happened, rather than inferring it secondhand.
• Work with product, business, data, and Digital Technology colleagues to set priorities, align on security and integration standards, and deliver solutions.
• Take part in field research, user testing, and feedback sessions that shape product decisions.
• Explain technical concepts, tradeoffs, and recommendations clearly to technical and non-technical audiences.
• Support a culture of experimentation, learning, and continuous improvement across the team.

The Stack
AWS, Cloudflare Workers and D1, TypeScript and React, Python, and LLM integration across hosted APIs and inference nodes. You need not have used all of it. You do need to read unfamiliar infrastructure documentation and ship by Thursday.

Key Qualifications / Experience

• 4-6 years of experience in software engineering, product engineering, or full-stack application development.
• You have shipped production software that people depended on, and been on the hook when it broke.
• Experience building across multiple layers of the stack, including front end, back end, APIs, databases, and cloud services.
• Strong proficiency in TypeScript, JavaScript, Python, or a similar language, and experience with modern web frameworks and cloud-native development, ideally on AWS.
• Familiarity with AI-enabled products, machine learning applications, large language models, or intelligent automation strongly preferred.
• Comfortable owning deploys and monitoring. Not an SRE, but not someone who hands off at the merge.
• You can hold a complex system in your head and reason about where it fails, not only where it works.
• You work independently, manage ambiguity, and balance multiple priorities as requirements change.
• Excellent problem-solving, communication, and collaboration skills.
• You would rather ask a cooperative manager what happened than infer it secondhand, and you have gathered requirements directly from users.
• Spanish proficiency preferred, but not required