Senior Customer Engineer

At FourKites we have the opportunity to tackle complex challenges with real-world impacts. Whether it’s medical supplies from Cardinal Health or groceries for Walmart, the FourKites platform helps customers operate global supply chains that are efficient, agile and sustainable.

Join a team of curious problem solvers that celebrates differences, leads with empathy and values inclusivity.

As a Senior Customer Engineer, you own the technical customer relationship end to end. You run discovery independently, design integration and agentic workflow architectures for complex enterprise problems, and deploy solutions live with customers — often before they know exactly how to articulate what they need. You write optimized, production-grade code at speed, grounded in strong data structures and algorithms fundamentals, because compressing the time from customer problem to working solution is how FDE delivers its value. You bring genuine innovation to hard problems — your solutions are technically sound, elegant, and often non-obvious. You are the primary technical contact for 2–4 major enterprise accounts, you mentor FDEs on the team, and you are building the skills that will take you into Staff-level technical leadership.

• →Own complex integration and AI agent implementations end-to-end — from technical discovery through go-live and post-launch enhancement — as the primary technical contact for 2–4 enterprise accounts
• →Design integration architectures with explicit attention to error handling, retry logic, observability, failure recovery, and multi-system authentication
• →Design and deploy agentic AI workflows that orchestrate supply chain operations — from requirements through production, including regression testing and validation before each customer deployment
• →Deploy AI agent workflows live with customers present — configuring and troubleshooting in the room during customer calls, not gathering requirements to build later
• →Run customer discovery sessions independently — hear a business problem and propose a technically credible, innovative solution on the spot without IM or management support
• →Use Claude, OpenAI, and other LLMs across the entire workflow — capturing requirements, designing integrations, generating integration specs, writing code, testing and deployment; the expectation is LLM-assisted work at every stage, not just at the keyboard
• →Represent FourKites from a technical lens during presales engagements — articulate integration architecture, agentic workflow capabilities, and platform extensibility to prospective enterprise customers alongside the Solutions and Sales teams
• →Join scoping and strategic customer calls alongside the SCA team to tackle the highest-complexity technical and product questions — come in with a point of view, not just answers
• →Perform code reviews on integration and AI workflow work from FDEs and enforce quality standards before deployment
• →Mentor FDEs — pair on hard problems, review their work consistently, and take accountability for their growth
• →Identify reusable integration patterns and AI workflow templates and formalize them for the team library
• →Scope and estimate level of effort for projects accurately and hold yourself accountable to those estimates
• →Collaborate with Implementation Managers, Customer Success Managers, Solutions Consultants, Product Managers, and Engineering to deliver seamless customer outcomes
  
  

• 5–8 years of software engineering experience, with meaningful depth in integration engineering, system design, or a customer-facing technical role — what matters is the complexity and ownership of what you have built
• Strong proficiency in Java (required) and one or more of: Python or Ruby - writes clean, production-grade code with test coverage, clear design rationale, and a standard other engineers can follow
• Strong foundations in data structures and algorithms — designs systems that perform at scale, reasons about complexity tradeoffs under pressure, and makes the right architectural call for high-throughput, low-latency integration scenarios
• Strong software design skills — architects integration and AI workflow systems that are modular, resilient, observable, and built to evolve; can articulate the design, defend the tradeoffs, and produce a diagram that makes it legible to others
• Writes optimized code at speed — takes a customer problem from discovery to deployed solution faster than traditional development cycles; the ability to compress the build cycle without compromising quality is what enables customers to move faster
• Innovative problem solver — brings genuine creativity to hard integration and AI workflow challenges; finds approaches that are technically sound, elegant, and often non-obvious; complexity doesn't slow you down, it sharpens your thinking
• Deep expertise in enterprise integration patterns and how to apply them across complex, multi-system — knows when to apply which approach and can justify the tradeoffs
• Hands-on experience designing and deploying agentic AI workflows end-to-end using LangGraph or equivalent — not configuring templates, architecting systems
• Uses Claude, OpenAI, or equivalent LLMs across the full workflow — requirements documentation, integration design, spec generation, code generation, testing and deployment; treats LLMs as a core engineering capability, not a productivity shortcut
• Proven ability to run technical discovery sessions with enterprise customers independently and translate ambiguous business requirements into concrete technical specs
• Comfortable deploying agentic workflows live in a customer call — handles configuration, troubleshooting, and edge cases in the moment
• Strong SQL proficiency — writes queries to investigate customer data issues and validate integration output

• Experience in supply chain, logistics, transportation, or B2B SaaS platforms is a strong plus
• Deep familiarity with enterprise integration patterns and a track record of applying them to complex, multi-system enterprise environments
• Familiarity with EDI standards, carrier integrations, TMS/WMS systems, and supply chain data flows
• Experience with low-code/no-code workflow automation platforms such as Pipedream, n8n, Temporal, or equivalent
• Snowflake experience and familiarity with large-scale data investigation across multi-tenant environments
• Proficient with Lucidchart, Miro, draw.io, or similar tools to document and communicate integration architectures and agentic workflow designs visually — customers and internal stakeholders should be able to read your design without needing to ask what it means