AI Engineer I

FourKites•Chicago, IL

About The Position

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. We are seeking an experienced AI Engineer to join our AI team, where you'll play a pivotal role in building and scaling our next-generation AI workforce platform. You'll work on cutting-edge agent-based systems that are transforming supply chain operations for Fortune 500 companies, delivering real business value through intelligent automation. What you'll be doing?

Requirements

1+ years software engineering, 1+ years in production AI/ML systems
Expertise in Python, PyTorch/JAX, and AI frameworks (LangChain, Transformers, PEFT)
Exposure to LLMs (GPT-4, Claude, Gemini) and SLMs (Phi, Llama, Mistral)
Hands-on experience in any of the below:
Fine-tuning techniques (LoRA, QLoRA, DPO, RLHF)
Vector databases and RAG architectures
Streaming systems and real-time processing
Security measures (prompt injection prevention, jailbreak detection)
Model optimization (quantization, distillation, pruning)
Background in distributed systems, Kubernetes, and cloud platforms
Good communication for technical and non-technical audiences
Data-driven decision making for model selection and cost optimization

Nice To Haves

Experience with document intelligence and multi-modal AI systems
Understanding of supply chain operations, EDI/API integrations
Knowledge of token economics and consumption-based pricing models
Familiarity with enterprise compliance requirements (GDPR, CCPA, SOC2)
Knowledge of GraphRAG and knowledge graph integration
Contributions to open-source AI projects (Hugging Face, Ollama)
Experience reducing inference costs by 50%+ through optimization
Familiarity with MoE architectures and constitutional AI approaches
Exposure to OCR pipelines and document extraction at scale
Exposure to specialized tools (vLLM, TGI, Triton, ONNX, TensorRT) is a bonus.

Responsibilities

Implement production-scale AI agent systems and orchestration frameworks (LangGraph, LangChain, similar architectures)
Optimize deployment strategies using both LLMs and SLMs based on use case requirements
Build natural language-configurable business process automation frameworks
Implement multi-modal AI systems for document understanding (tables, charts, layouts)
Deploy and optimize LLMs/SLMs in production with fine-tuning techniques (LoRA, QLoRA, DPO)
Implement quantization strategies (INT8, INT4) and model distillation for edge deployment
Build evaluation frameworks including LLM-as-judge systems and regression testing
Create semantic caching and embedding-based retrieval systems
Develop GraphRAG and long-context handling strategies (100k+ tokens)
Develop scalable microservices with comprehensive observability (LangSmith, Arize, custom telemetry)
Build secure multi-tenant systems with prompt injection prevention and output validation
Implement cost optimization through intelligent model routing and fallback strategies
Develop document processing pipelines with OCR and layout understanding
Create event-driven architectures for real-time shipment tracking and exception handling
Building specialized AI agents solving supply chain problems
Fine-tuning domain-specific models for supply chain terminology
Implementing hybrid architectures combining cloud LLMs with edge SLMs
Creating secure document intelligence systems for Fortune 500 clients
Developing real-time exception handling for shipment tracking
Building observability and evaluation frameworks for agent performance
Designing fallback strategies and multi-provider redundancy
Working with Customer facing teams to understand customer requirements and tuning AI solutions and providing support for customer queries.