Product & Deployment Engineer

Pallet•San Francisco, NY

3d•Onsite

About The Position

Pallet is building AI Agents to transform logistics — a $12 trillion global industry. We’ve raised $50M from top investors, including General Catalyst, Bessemer Venture Partners, and Bain Capital Ventures. In under two years, we’ve achieved 700% revenue growth and are just getting started. Our mission is to increase the efficiency of the global supply chain by automating the manual workflows that slow logistics teams down — from scheduling and appointment setting to data entry and load management. Our flagship platform provides end-to-end visibility, control, and optimization, while our newest product, CoPallet, introduces AI Agents that can understand and execute requests in real time, and integrate directly with customer systems. As logistics providers look to generative AI to drive efficiency, many are turning to Pallet to lead the way. With deep industry expertise and cutting-edge AI capabilities, we’re positioned to build the next $10B company in logistics. Join us and work alongside leaders from Google, DoorDash, YC, and more to shape the future of logistics tech. About The Role We’re hiring Product & Deployment Engineers to deploy production AI agents inside some of the world’s largest logistics companies. You will work directly with customer operators, engineers, and executives to understand how critical workflows actually run, then design and ship AI systems that automate them. One week, you may be reverse engineering a legacy transportation management system with no documentation. The next week, you may be debugging production failures onsite with a Fortune 500 customer and shipping fixes the same day. This is a uniquely high-leverage engineering role. You’ll sit at the intersection of product, infrastructure, and customer operations, owning deployments from the first integration through production scale. The problems are messy, ambiguous, and highly consequential. The engineers who thrive here enjoy operating in the real world. They care more about delivering outcomes than building perfect abstractions, and they’re excited by the challenge of making complex systems work in environments they don’t fully control. Every deployment teaches us something new about how logistics companies operate. The insights you uncover won’t just help individual customers—they’ll directly shape the product roadmap and influence what we build next. This role is for you if You enjoy debugging messy real-world systems more than building pristine internal abstractions. You like working directly with customers and uncovering solutions in ambiguous environments. You move quickly, make pragmatic decisions, and optimize for outcomes over elegance. You want ownership of real business impact, not just tickets or isolated services. You enjoy being the person who figures things out when documentation is incomplete, and the answer isn’t obvious. This role is likely not for you if You’re primarily interested in model research or pure ML experimentation. You prefer highly scoped platform work with limited customer interaction. You want detailed specifications before starting a project. You prefer remote-first environments or minimal travel.

Requirements

2–5 years of experience building and owning production systems in high-growth startups or similarly demanding environments.
Strong experience working with APIs, authentication systems, integrations, and event-driven architectures.
Proven ability to debug complex systems under real production constraints.
Comfortable operating with ambiguity and incomplete information.
Strong written and verbal communication skills.

Nice To Haves

Experience working directly with customers, partners, or external stakeholders is a plus.
Bonus: experience with logistics, supply chain software, ERP systems, automation platforms, or workflow tooling.

Responsibilities

Reverse engineer undocumented APIs, ERPs, TMS platforms, and internal systems with minimal guidance.
Design and build integrations between customer environments and Pallet’s AI platform.
Debug production failures across distributed systems, data pipelines, authentication layers, and third-party dependencies.
Work onsite with customers (~25% travel) to diagnose issues, deploy fixes, and drive successful launches.
Own customer go-lives end-to-end, from technical discovery through production stability.
Identify recurring implementation patterns and turn them into reusable product capabilities.
Influence the roadmap by translating customer problems into platform improvements.