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Pallet

Software Engineer, Agent Delivery

San Francisco$135k–$180kfull-timemidAdded today

About this role

Pallet is seeking a Software Engineer to deploy production AI agents within major supply chain companies. You'll own end-to-end customer deployments, designing and building reliable agent workflows while integrating them into complex, undocumented customer environments—turning field learnings into reusable platform capabilities.

What you'll do

  • Lead production AI agent deployments from discovery through launch, owning technical outcomes
  • Design integrations connecting Pallet agents to customer systems, APIs, and data sources
  • Debug and optimize production systems in business-critical, often fragmented environments
  • Translate customer workflows and business requirements into clear technical solutions
  • Partner with customers across engineering, operations, and leadership to understand real-world problems
  • Convert individual deployment patterns into reusable product features and implementation frameworks

What they're looking for

  • Software engineering and systems design
  • API integration and data pipeline development
  • AI/LLM agent design and evaluation
  • Debugging and troubleshooting production systems
  • Technical communication with non-engineering stakeholders
  • Rapid prototyping and iteration
  • Supply chain domain knowledge (preferred)
  • Cloud infrastructure and deployment practices

Benefits

  • Competitive salary ($135,000–$180,000)
  • Full-time position with onsite presence in San Francisco or New York
  • Direct impact on $12 trillion global supply chain industry
  • Work with AI agents and cutting-edge generative AI technology
  • Collaboration with experienced leadership from Google, DoorDash, and YC
  • Opportunity to shape core product strategy through customer feedback
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Pallet

Pallet builds AI agents that automate workflows and enhance operations for large logistics companies. The company is hiring product engineers, deployment specialists, and sales engineers to implement these solutions with enterprise clients and drive product development based on real-world deployments.

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Likely interview questions

  • Tell us about a time you debugged a production issue in an unfamiliar or undocumented system. How did you approach it?
  • Describe your experience integrating with third-party APIs or legacy systems. What challenges did you encounter?
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