AI Engineer, FourKites

• 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
• (Bonus) Security measures (prompt injection prevention, jailbreak detection)
• (Bonus) Model optimization (quantization, distillation, pruning)
• (optional) Background in distributed systems, Kubernetes, and cloud platforms
• Professional Skills
• Good communication for technical and non-technical audiences
• (Bonus) Data-driven decision making for model selection and cost optimization
• FourKites is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. If you're excited about this role but don't meet every requirement, we encourage you to apply

Desirable

• 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
• Technical Leadership
• 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)
• AI/ML Implementation & Optimization
• 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)
• System Architecture & Engineering
• 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
• You'll directly contribute to AI initiatives generating millions in revenue while shaping systems processing millions of transactions daily. Be at the forefront of production AI optimization, balancing performance, cost, and latency for enterprise customers
• Technical Environment
• Models: GPT-4, Claude, Gemini, Llama 3, Mistral, Phi-3, custom fine-tuned models
• Fine-tuning: LoRA/QLoRA, PEFT, DeepSpeed, bitsandbytes, Axolotl
• Infrastructure: Kubernetes, AWS SageMaker/Bedrock, GPU clusters, edge devices
• Frameworks: LangChain, LangGraph, vLLM, FastAPI, Transformers
• Observability: LangSmith, Weights & Biases, custom telemetry
• Data: PostgreSQL, Redis, Vector DBs, Kafka, feature stores