Senior Engineering Manager

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 Senior Engineering Manager to lead our AI/ML engineering teams in building cutting-edge artificial intelligence solutions. This role requires a unique blend of technical expertise in AI/ML, proven engineering leadership, and strategic thinking to drive innovation at scale.Key ResponsibilitiesTechnical LeadershipDefine and execute the technical strategy for AI/ML initiatives across multiple product areasOversee the design and architecture of scalable ML systems, from data pipelines to model deploymentDrive decisions on technology stack, frameworks, and infrastructure for AI/ML workloadsEnsure engineering excellence through code reviews, design reviews, and technical mentorshipStay current with AI/ML research and industry trends to inform strategic decisionsPeople ManagementLead, mentor, and grow a team of 15+ AI engineers, data scientists, and software engineersBuild high-performing teams through hiring, performance management, and career developmentFoster a culture of innovation, collaboration, and continuous learningConduct regular 1:1s, performance reviews, and career development conversationsChampion diversity, equity, and inclusion initiatives within the engineering organizationStrategic Planning & ExecutionPartner with Product Management to define AI product roadmap and prioritiesTranslate business objectives into technical initiatives and measurable outcomesManage multiple concurrent AI/ML projects from conception to production deploymentEstablish and track KPIs for team performance, model quality, and system reliabilityBalance innovation with pragmatic delivery to meet business deadlinesCross-functional CollaborationWork closely with Data Science, Product, Design, and other engineering teamsCommunicate technical concepts and trade-offs to non-technical stakeholdersRepresent engineering in executive discussions and strategic planning sessionsBuild relationships with external partners, vendors, and research institutionsDrive alignment across teams on AI ethics, responsible AI practices, and governanceOperational ExcellenceEstablish best practices for ML model development, testing, and deploymentImplement MLOps practices for continuous integration and deployment of ML modelsEnsure compliance with data privacy regulations and AI governance policiesDrive improvements in model monitoring, A/B testing, and experimentation frameworksManage engineering budget and resource allocationRequired QualificationsExperience13+ years of software engineering experience, with 5+ years focused on ML/AI systems5+ years of engineering management experience, including managing managersProven track record of shipping ML products at scale in production environmentsExperience with full ML lifecycle: data collection, feature engineering, model training, deployment, and monitoringTechnical SkillsDeep understanding of machine learning algorithms, deep learning, and statistical methodsProficiency in ML frameworks (TensorFlow, PyTorch, JAX) and programming languages (Python, Scala, Java)Experience with distributed computing frameworks (Spark, Ray) and cloud platforms (AWS, GCP, Azure)Knowledge of MLOps tools and practices (Kubeflow, MLflow, Airflow, Docker, Kubernetes)Understanding of data engineering, ETL pipelines, and big data technologiesLeadership CompetenciesDemonstrated ability to build and scale engineering teamsStrong communication skills with ability to influence at all levels of the organizationExperience driving technical strategy and making architectural decisionsTrack record of successful cross-functional collaboration and stakeholder managementAbility to balance technical depth with business acumenPreferred QualificationsAdvanced degree (MS/PhD) in Computer Science, Machine Learning, or related fieldDeep experience with Large Language Models (LLMs), Small Language Models (SLMs), and generative AI applicationsExpertise in building production AI agent systems:Multi-agent architectures and swarm intelligenceMemory systems: short-term, long-term, episodic, and semantic memoryPlanning algorithms: hierarchical planning, goal decomposition, and backtrackingTool use and function calling optimizationAgent communication protocols and coordination strategiesExperience with advanced agent frameworks: DSPy, Guidance, LMQL, Outlines for constrained generationKnowledge of prompt engineering techniques: few-shot, chain-of-thought, self-consistency, constitutional AIExperience with RAG architectures: vector stores, hybrid search, re-ranking, and query optimizationExpertise in training techniques: supervised fine-tuning, RLHF, DPO, PPO, constitutional AI, and synthetic data generationExperience with parameter-efficient fine-tuning methods: LoRA, QLoRA, prefix tuning, and adapter layersKnowledge of model optimization techniques: quantization (INT8, INT4), distillation, pruning, and flash attentionExtensive experience in dataset curation for LLM training:Web-scale data processing (Common Crawl, C4, RefinedWeb methodologies)Creating instruction-tuning datasets (Alpaca, Dolly, FLAN-style formats)Building preference datasets for RLHF/DPO trainingDomain adaptation and specialized corpus creationMulti-lingual and code dataset preparationKnowledge of data mixing strategies, replay buffers, and curriculum learning for optimal trainingExperience with data augmentation techniques: paraphrasing, back-translation, and synthetic data generation using LLMsExpertise in data decontamination and benchmark pollution preventionExperience with workflow automation platforms: n8n, Zapier, Make for business process automationKnowledge of enterprise integration patterns: event-driven architectures, saga patterns, and CQRSStrong background in data science: statistical analysis, A/B testing, experimentation design, and causal inferenceExperience with data mesh architectures and building self-serve data platformsExpertise in data quality frameworks, data contracts, and SLA management for data pipelinesExperience with vector databases (Pinecone, Weaviate, Qdrant, Milvus, ChromaDB, FAISS) and embedding systemsKnowledge of privacy-preserving ML techniques: differential privacy, federated learning, secure multi-party computationBackground in specific AI domains: NLP, Computer Vision, Recommendation Systems, or Reinforcement LearningExperience with LLM evaluation frameworks and benchmarking (HELM, EleutherAI eval harness, BigBench)Hands-on experience with popular LLM frameworks: Hugging Face Transformers, vLLM, TGI, Ollama, LiteLLMExperience with dataset processing tools: Datasets library, Apache Beam, Spark NLPPublications or contributions to open-source ML projectsExperience in high-growth technology companies or AI-first organizationsKnowledge of AI safety, ethics, and responsible AI practicesExperience with multi-modal models and vision-language modelsWhat We OfferOpportunity to work on cutting-edge AI technology with real-world impactCompetitive compensation package including equityAccess to state-of-the-art computing resources and research toolsBudget for conferences, training, and professional developmentCollaborative environment with talented engineers and researchersFlexible work arrangements and comprehensive benefitsWho we are:FourKites, the leader in AI-driven supply chain transformation for global enterprises and pioneer of advanced real-time visibility, turns supply chain data into automated action. FourKites' Intelligent Control Tower breaks down enterprise silos by creating a real-time digital twin of orders, shipments, inventory and assets. This comprehensive view, combined with AI-powered digital workers, enables companies to prevent disruptions, automate routine tasks, and optimize performance across their supply chain. FourKites processes over 3.2 million supply chain events daily — from purchase orders to final delivery — helping 1,600+ global brands prevent disruptions, make faster decisions and move from reactive tracking to proactive supply chain orchestration.Working at FourKitesWe provide competitive compensation with stock options, outstanding benefits and a collaborative culture for all employees around the globe, including: 5 global recharge days, in addition to standard holidays, and a hybrid, flexible approach to work.Parental leave for all parents, an annual wellness stipend and volunteer days also provide you with time and resources for self care and to care for others.Opportunities throughout the year to learn and celebrate diversity.Access to leading AI tools and foundation models, with the freedom to experiment and find creative ways to be more effective in your roleAnd we're always listening for new ways to support everyone in and out of the office.