Forward-Deployed Engineer

Job Overview Work on meaningful problems at the core of global trade, helping modernize the systems that move essential resources around the world. Join early and have outsized impact as part of a small, high-trust team building product, process, and company foundations together. Own customer outcomes end to end and see your work directly shape real operational improvements in the field. Tackle technically challenging problems that span AI, workflow automation, systems integration, and real-world operations. Collaborate closely with customers and teammates who care deeply about execution, clarity, and building software that truly gets used. Location Details San Francisco, CA, United States (In-Person, 4 days onsite; up to 30% travel) About Us At CommodityAI, we build purpose-built AI for the commodities industry—one of the world’s most operationally complex and infrastructure-critical sectors. Our platform automates document-heavy workflows across trading, logistics, finance, and compliance, turning messy data from emails, PDFs, and legacy systems into clean, actionable records. By combining document intelligence, workflow automation, and system integrations, we help commodity businesses reduce manual work, improve accuracy, and operate with greater speed and control. We’re building intelligence into the foundation of global trade. Role Introduction As a Forward‑Deployed Engineer, you’ll sit at the intersection of engineering, product, and customer delivery. You’ll own the technical rollout of CommodityAI at customer sites, taking deployments from early discovery through stable production. This is a highly hands‑on role for someone who can translate ambiguity into reliable automation, work closely with traders, operators, and executives, and build trust through clear execution. You’ll help customers modernize mission‑critical workflows while shaping the way our product scales across the commodities ecosystem. What You'll Do Own technical delivery across multiple customer deployments, from initial scoping and prototype design through production launch and adoption. Build, configure, and refine AI agents, reasoning workflows, and structured data pipelines to match each customer’s operational logic. Partner directly with traders, schedulers, operators, logistics teams, and senior stakeholders to understand workflows and translate requirements into working solutions. Lead customer-facing implementation calls, including requirements gathering, progress reviews, issue resolution, and user enablement. Manage data flows and integrations between CommodityAI and customer systems such as CTRMs, ERPs, and other internal platforms. Make sound trade-offs across scope, speed, and quality to keep projects moving while maintaining reliability and accuracy. Turn recurring deployment patterns into reusable playbooks, templates, and implementation standards that improve delivery over time. What You Bring 5+ years of engineering, solutions engineering, or technical implementation experience in roles that included direct customer engagement. Strong coding ability across production systems, ideally with Python, TypeScript, or comparable backend and frontend technologies. Experience delivering complex software in enterprise environments, with the judgment and structure needed to navigate high‑stakes customer deployments. Ability to work through ambiguous requirements, break down operational problems, and build practical, dependable solutions. Clear communication skills and confidence presenting technical concepts to both end users and executive stakeholders. Familiarity with AI‑powered products, LLMs, or generative systems, including an understanding of how model behavior affects product performance and user trust. A high‑ownership mindset, strong follow‑through, and comfort operating in an early‑stage environment where priorities evolve quickly. Nice to Have Experience in commodities, supply chain, logistics, trading operations, or other document‑heavy operational industries. Background integrating with enterprise systems such as CTRMs, ERPs, or internal workflow tools. Experience designing data extraction, classification, or reconciliation workflows from unstructured sources like emails and PDFs. A track record of creating reusable deployment frameworks, implementation tooling, or customer onboarding standards. If you’re excited by customer‑facing engineering, operational complexity, and the opportunity to build AI systems that matter in the real world, we’d love to hear from you. #J-18808-Ljbffr Career Genie, Inc