Forward-Deployed Engineer

Identify patterns across problems and help convert them into reusable platform functionality. Collaborate closely with Product, Design and core Engineering, and with our Data and Infrastructure teams who will support your builds, while retaining ownership of delivery. Communicate technical decisions, limitations and trade-offs clearly to technical and non-technical stakeholders, up to executive level. Maintain appropriate standards for security, reliability, data protection and maintainability, and support solutions through implementation and early adoptions Requirements Strong professional software engineering experience across the full lifecycle, comfortable taking a problem from discovery through to independently building, deploying and running it in production. Strong skills in at least one modern programming language, such as TypeScript, JavaScript, Python, Java, Kotlin or C#. Some familiarity with Kotlin or Python, our primary languages, is valued but not essential. Experience

building and consuming APIs, webhooks and system integrations. Experience working with databases, data models and event-driven workflows. Fluent use of AI-assisted development tools as a core part of how you build. This is essential to the role. Strong product judgement: understands unfamiliar business processes quickly, embeds with a team to distil what matters, and separates the immediate user request from the underlying problem. Comfortable working with ambiguity and making sensible decisions without waiting for perfect requirements, with a bias toward action, experimentation and iterative delivery. Confidence working directly with operational users and senior stakeholders, collaborating across Product, Design, Engineering and our Data and Infrastructure teams, and explaining technical concepts in clear, practical language. Strong ownership, including responsibility for whether the solution achieves the intended outcome rather than only whether the code was delivered. Good understanding of software quality, observability, testing, security and maintainable architecture. Experience in freight, logistics or supply chain, or in another B2B SaaS or operational technology environment is a plus. Experience building workflow automation or orchestration, for example with tools such as n8n is a plus. Experience with large language model applications and unstructured-data problems such as document extraction or email classification is a plus. Experience integrating with ERP, transport-management, warehouse-management or internal operational systems is a plus. Experience in a solutions engineering, implementation, internal-tools or forward-deployed role, including taking bespoke solutions and turning them into product is a plus. Familiarity with cloud infrastructure, Terraform, CI/CD and production support, ideally in an early-stage or high-growth environment is a plus. Core Competencies Demonstrates strong software engineering skills across the full lifecycle, with a focus on building and deploying solutions that integrate with APIs and leverage AI-assisted development tools. Capable of collaborating with cross-functional teams and communicating technical concepts effectively to both technical and non-technical stakeholders. Highest-signal resume keywords Software Engineering Experience API Development and Integration AI-Assisted Development Tools Freight and Supply Chain Experience Workflow Automation and Orchestration ATS Optimization Keywords Hard Skills TypeScript JavaScript Python Java Kotlin API Development Database Management Event-Driven Workflows Software Quality Assurance Testing and Observability Soft Skills Strong Product Judgement Collaboration Communication Ownership Comfort with Ambiguity Industry Keywords Freight Logistics Supply Chain B2B SaaS Operational Technology Tools & Technologies N8n Cloud Infrastructure Terraform CI/CD ERP Systems #J-18808-Ljbffr

Embed with operations teams and internal stakeholders, typically for a few months at a time, to understand complex freight and supply-chain workflows. Translate loosely defined business problems into clear technical solutions, deciding when to extend existing functionality and when to build new. Turn manual, spreadsheet and inbox-based decisions into platform logic that can be automated and, over time, increasingly handled by AI. Build and deploy prototypes, automations and production-ready features, integrating with internal Zencargo services, carrier platforms and third-party APIs. Use AI and modern development tools both to accelerate delivery and as a core part of the solutions you build. Work with structured and unstructured data, including emails, documents, purchase orders, shipment data and operational events. Test and measure solutions against real workflows and user feedback, looking for reduced manual effort, better accuracy, faster processing and a smoother-running business.