Architect end-to-end integration solutions for complex enterprise environments spanning ERP (SAP, Oracle, Blue Yonder, Manhattan), OMS, WMS, TMS, and YMS platforms, working directly with customer technical teams to translate business problems into implementable designs
Design and build data pipelines (batch and streaming) using messaging infrastructure and event-driven architectures that enable real-time supply chain data flow at enterprise scale
Build, extend, and optimize agentic AI workflows using LangGraph, LangChain, and related frameworks, integrating LLM-powered automation into customer-facing supply chain operations
Design microservices architectures for integration layers: API gateway patterns, service decomposition, inter-service communication, containerization (Docker, Kubernetes), and cloud-native deployment on AWS, Azure, or GCP
Develop and maintain APIs (REST, GraphQL) and integration middleware connecting customer enterprise systems to the FourKites platform
Own technical proof-of-concepts for new integration patterns, AI-powered workflows, and platform capabilities, taking them from prototype to production-ready
Define reference architectures and reusable integration patterns that scale across customers, covering traditional EDI/file-based integrations (X12, EDIFACT, flat file, SFTP/AS2) through modern event-driven and AI-augmented approaches
Establish engineering standards for data quality, observability, error handling, retry logic, and scalability across all customer integrations
Drive technical decisions on integration approach selection: real-time streaming vs. batch ETL, synchronous vs. asynchronous patterns, push vs. pull models, grounded in customer system constraints and business requirements
Evaluate emerging technologies and integration patterns, building team capability in AI/ML engineering, cloud-native architectures, and modern data infrastructure
Build and maintain trusted-advisor relationships with technical and executive stakeholders at strategic accounts, spanning the full lifecycle from initial scoping through production optimization
Provide solutions architecture consultation during pre-sales: scoping complex integration and AI agent deployments, identifying technical risks, sizing effort, and translating platform capabilities into customer business value
Partner with R&D Teams to shape the platform roadmap based on field experience, advocating for integration-layer and AI capability improvements grounded in real customer implementation data
Contribute to external thought leadership: reference architectures, technical blog posts, conference presentations, and customer-facing best practice documentation
Serve as the senior escalation point for the hardest integration and AI engineering challenges, both internal and customer-facing
Mentor customer engineers (onshore and offshore) through design reviews, code reviews, pairing sessions, and architecture walkthroughs, raising the technical bar across the team
Lead by building: prove out new approaches hands-on before asking the team to adopt them
Define and track integration quality and engineering productivity metrics
Requirements
12+ years in software engineering, data engineering, or solutions architecture, with significant time in customer-facing roles designing and delivering enterprise-grade systems
Hands-on builder: you write production code, build data pipelines, debug distributed systems, and architect solutions, not just review them
Deep expertise in data pipeline and messaging infrastructure: Kafka, RabbitMQ, SQS/SNS, or comparable; hands-on experience designing streaming and batch data flows at scale
Strong API engineering skills: designing, building, and scaling REST and GraphQL APIs; experience with API gateway patterns, rate limiting, versioning, and authentication protocols
Hands-on AI engineering experience: building agentic workflows and LLM-powered applications using LangGraph, LangChain, or equivalent frameworks; practical understanding of prompt engineering, tool orchestration, retrieval-augmented generation, and agent evaluation
Microservices architecture expertise: service decomposition, inter-service communication (gRPC, async messaging), containerization (Docker, Kubernetes), and cloud-native deployment on AWS, Azure, or GCP
3+ years of experience in logistics, supply chain, or transportation technology; working understanding of supply chain data flows (orders, shipments, inventory, tracking events, carrier integrations)
Working knowledge of enterprise integration patterns: EDI (X12, EDIFACT), middleware platforms (MuleSoft, Dell Boomi, Informatica), file-based protocols (SFTP, AS2), and data transformation/ETL
Solutions architect mindset: you start with the customer's business problem, design the right architecture, and can present the approach to both engineers and C-suite stakeholders with equal clarity
Bachelor's or Master's degree in Computer Science, Engineering, Math, or equivalent experience.
Tech Stack
AWS
Azure
Cloud
Distributed Systems
Docker
ERP
ETL
Google Cloud Platform
GraphQL
GRPC
Informatica
Kafka
Kubernetes
Microservices
Oracle
RabbitMQ
Benefits
Medical, Dental & Vision benefits starting on first day of employment
401k Retirement savings with employer match
Bonus and incentive compensation as well as employee stock option program
Employer paid life insurance and short term disability insurance
Generous PTO, global recharge days, and volunteer days
Paid parental leave for all parents
Family planning and inclusive wellbeing resources
Technology reimbursement
Commuter benefits for in-office employees (Chicago)