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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior AI Engineer - **Company:** Crate and Barrel - **Location:** Northbrook, IL, United States (Remote available) - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Agile Methodology, Artificial Intelligence, Amazon Web Services, Big Data, BigQuery, C Sharp (Programming Language), Cloud Computing, Code Review, Information Systems, Continuous Integration, Information Engineering, Data Infrastructure, DevOps, Distributed Computing Environment, Data Flow Control, Monitoring of Systems, Python (Programming Language), Machine Learning, Scrum Methodology, Tensorflow, Standard Sql, Azure Machine Learning, Software Engineering, Systems Integration, Management of Software Versions, Google Cloud, Cloud Monitoring, Pytorch, Multi-Agent Systems, Apache Spark, Deep Learning, Build Server, Pandas, Build Management, Containerization, Scikit Learn, Kubernetes, Information Technology, Optimization Algorithms, Machine Learning Operations, Virtual Agents, Software Coding, Software Version Control, Apache Beam, Docker - **Published:** August 28, 2026 - **Apply:** https://www.techcareers.com/job.asp?id=3367804131&tx=KP6565FFJ&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54 ## About the Role * Strong hands-on experience with Google Cloud Platform for ML: Vertex AI (Training, Pipelines, Model Registry, Endpoints, Model Monitoring), BigQuery, Cloud Run, GKE, and Cloud Build * Strong proficiency in Python and C#, with deep experience in core ML frameworks (TensorFlow, PyTorch, scikit-learn) * Strong knowledge of Agentic AI frameworks: Google ADK, AutoGen, LangChain, LlamaIndex, and experience integrating with Gemini/Vertex AI foundation models * Strong understanding of distributed training, model serving architecture, and best practices for scaling ML applications on GCP * Hands-on experience with MLOps tools (Vertex AI Pipelines, MLflow, DVC, Kubeflow) and containerization (Docker, Kubernetes/GKE) * Direct experience building and deploying ML solutions on Google Cloud (Vertex AI required); familiarity with AWS SageMaker or Azure ML a plus * Solid theoretical foundation in machine learning, statistics, and optimization techniques * Proficient in SQL (BigQuery), Pandas, and large-scale data processing (Dataflow/Apache Beam, Spark) * Deep understanding of agile methodologies * Strong communication, collaboration, and technical leadership skills * Proven ability to mentor and guide other engineers * Strong software engineering fundamentals: coding standards, code reviews, source control, testing, and operations * Excellent problem-solving and cross-functional communication skills, * Bachelor's degree in Computer Science, Software Engineering, Information Systems, or a related field (or equivalent practical experience) * 5+ years of experience in machine learning engineering * Proven track record of successfully designing, implementing, and deploying at least 2-3 significant ML models into a high-availability production system, Euromarket Designs, Inc., which does business as Crate and Barrel and CB2, will be referred to as "the Company". The Company is deeply committed to working with and providing reasonable accommodations to individuals with disabilities. If you need a reasonable accommodation for any part of the application process, or in order to perform the essential functions of a position, please contact the location you are applying to here and ask to speak with a manager regarding the nature of your request. The Company is an equal opportunity employer; applicants are considered for all positions without regard to race, color, religious creed, sex, national origin, citizenship status, age, physical or mental disability, sexual orientation, gender identity, marital, parental, veteran or military status, unfavorable military discharge, or any other status protected by applicable federal, state or local law. The Company participates in E-Verify and will provide the federal government with your Form I-9 information to confirm that you are authorized to work in the US. State / City Compliance: The Company will consider for employment qualified applicants with criminal history, including arrest and conviction records, in accordance with the Los Angeles Fair Chance Initiative for Hiring and the San Francisco Fair Chance Ordinance. ## Description A day in the life as a Senior AI Engineer... * Design, develop, train, and fine-tune complex ML models (deep learning and classical techniques) to solve high-priority business problems, with deployment targeted primarily on Google Cloud Platform * Own end-to-end model deployment on GCP (Vertex AI, GKE, Cloud Run), ensuring performance, scalability, and stability under low-latency production requirements * Build and maintain MLOps pipelines on GCP (Vertex AI Pipelines, Cloud Build, Artifact Registry) for automated training, testing, versioning, and CI/CD * Design and build agentic AI systems and multi-agent workflows using frameworks such as Google ADK, LangChain, LlamaIndex, or AutoGen, integrated with GCP services (Vertex AI, Gemini models) * Write clean, well-tested, production-grade Python and C# code; participate actively in code reviews to uphold engineering standards. * Profile and optimize training and inference speed and cost, particularly for large datasets and distributed/constrained environments on GCP infrastructure * Author technical user stories covering the full ML development lifecycle * Actively participate in and help drive team ceremonies, sprint planning, and continuous process improvement * Partner with Data Engineering to define data infrastructure, features, and pipelines (BigQuery, Dataflow, Pub/Sub) needed for training and serving * Partner with DevOps and Cloud teams to build reliable, cost-optimized ML solutions on GCP * Collaborate continuously with product owners and stakeholders to refine technical solutions and roadmaps within an agile framework * Implement monitoring dashboards (Vertex AI Model Monitoring, Cloud Monitoring) to track drift, accuracy, latency, and cost, addressing issues proactively * Proactively identify, develop, and validate new features to improve model performance and generalization * Mentor engineers on ML and GCP best practices, and provide technical leadership on architecture decisions. ## Related Videos - [Coffee with Developers - Maria Apazoglou](https://www.wearedevelopers.com/videos/1209-coffee-with-developers-maria-apazoglou) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [Advanced Typing in TypeScript](https://www.wearedevelopers.com/videos/496-advanced-typing-in-typescript) - [Agentic employees in world's most downloaded FinTech app](https://www.wearedevelopers.com/videos/100123-agentic-employees-in-world-s-most-downloaded-fintech-app) - [Docker build without Docker](https://www.wearedevelopers.com/videos/100114-docker-build-without-docker) ## Related Articles - [Got AI ideas but no money? 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