project44

project44

Senior Forward Deployed Engineer

Chicago · Senior

Sponsorship not specifiedDetected 5 days ago
DockerKubernetesKafkaSparkAgentic AILogisticsProcurementERP

About the role

  • You'll be embedded directly with high-value LSP accounts - owning integration architecture, customizing agent workflows, and serving as the ground truth between how LSPs actually operate and how our product team thinks they do.
  • Your job is to transform logistics from a reactive service into a programmable network - replacing manual workflows with autonomous agent-to-agent coordination.
  • What you learn in the field shapes the roadmap.

Responsibilities

  • Own end-to-end integration for dedicated LSP accounts - configure bi-directional webhooks and event-driven pipelines so AI agents can read, act, and write data into customer TMS, WMS, and ERP systems instantly
  • Build event-driven pipelines (Kafka/PubSub) that carry agent intent at the scale of millions of logistics events per day
  • Serve as the ground truth - we can't build a world-class product in a silo. Your field observations directly inform what gets on the roadmap and when
  • Together, we're building something extraordinary-learn, grow, and thrive in our fast-paced, transformative environment.
  • As we work to deliver a truly world-class product, we're intentionally building teams that reflect the unique communities we serve.

Requirements

  • 5+ years in software engineering, solutions engineering, or technical implementation in a customer-facing role
  • Experience with event-driven architecture and stream processing (Kafka, PubSub, or similar)
  • Hands-on integration experience with TMS, WMS, or ERP systems
  • Mastery of API-first design and bi-directional webhook configuration
  • Strong debugging skills across distributed, agent-driven workflows
  • Deep domain knowledge in logistics - freight procurement, load tendering, carrier management, and exception handling. LSP customers don't trust engineers who don't understand their world. You need to speak their language to earn the right to change how they work.

Nice to have

  • Experience with agentic AI systems - context feeding, prompt engineering, tool invocation, stateful agents
  • Prior experience in a forward-deployed or field engineering role
  • Containerization and orchestration (Docker, Kubernetes)
  • You take ownership of outcomes, not just deliverables
  • You bring back what you see in the field and use it to make the product better
  • You move fast, iterate in the open, and don't wait for perfect conditions
  • You can translate technical complexity to both engineers and LSP operators without losing either audience
  • Work Authorization: Candidates must be authorised to work in the US without current or future employer-sponsored visa support.

Skills

  • Why p44LSP.ai?
  • For years, project44 focused on global shippers as our core customer.
  • That focus worked.
  • Our Shipper business is a category leader growing 20% year-over-year.
  • That strength is what makes the next chapter possible.
  • Shippers and LSPs are fundamentally different businesses.
  • Logistics Service Providers - freight forwarders, brokers, and 3PLs - sell logistics as their product.
  • Their software is their competitive edge.
  • Forward-deployed engineering.
  • AI coding tools across the workflow.
  • Agents as the product surface.
  • The LSP market is moving fast.

Company info

  • At project44, we're designing the future of how the world moves.
  • We are looking for candidates who are enthusiastic and committed to joining our team on-site, in our beautiful headquarters 3 days a week.

Equal opportunity

  • project44 is an equal opportunity employer.
  • equal opportunity employer.
  • For any accommodation needed during the hiring process, please email recruiting@project44.com.

Visa & Work Authorization

  • Candidates must be authorised to work in the US without current or future employer-sponsored visa support.

This listing is sourced directly from project44's careers page and normalized into a canonical job model.