[Remote] Lead AI Engineer

Note: The job is a remote job and is open to candidates in USA. Dice is a leading technology company specializing in AI solutions, and they are seeking a Lead AI Engineer to define and maintain AI/ML architecture on their Databricks Lakehouse. The role involves overseeing the delivery of AI/ML use cases, providing technical leadership, and ensuring compliance with engineering standards.ResponsibilitiesDefine and maintain the end-to-end AI/ML architecture on Primoris' Databricks Lakehouse, including feature engineering, model training, evaluation, deployment, and monitoring pipelinesDesign scalable, secure, and cost-optimized AI/ML and GenAI patterns that integrate with the Medallion architecture, Unity Catalog, and downstream BI and operational systemsArchitect and implement MLflow-based model lifecycle management (experiment tracking, model registry, versioning, and deployment) across development, staging, and production environmentsEvaluate and recommend AI/ML frameworks, foundation models, vector databases, and GenAI tooling (e.g., LangChain, LlamaIndex, Azure OpenAI, Semantic Kernel) aligned to Primoris' use cases and platform standardsPartner with enterprise architecture, security, and infrastructure teams to ensure AI/ML systems align with broader platform, integration, and compliance standardsLead the end-to-end delivery of AI/ML use cases from requirements and data exploration through model development, validation, deployment, and production monitoringServe as the first point of contact for technical challenges or escalations related to AI/ML workloads in development and production, including triage, root cause analysis, and remediationProvide technical leadership and delivery oversight across hybrid teams including internal engineers, consulting partners, and offshore resources, ensuring clear accountability and consistent outcomesEstablish and champion AI/ML engineering standards (experiment reproducibility, model versioning, CI/CD for ML, automated testing, observability, and incident runbooks) to ensure production-grade deliveryDefine and implement model monitoring frameworks to detect drift, degradation, and anomalies in production AI/ML systems, with appropriate alerting and retraining triggersSkillsDefine and maintain the end-to-end AI/ML architecture on Primoris' Databricks Lakehouse, including feature engineering, model training, evaluation, deployment, and monitoring pipelinesDesign scalable, secure, and cost-optimized AI/ML and GenAI patterns that integrate with the Medallion architecture, Unity Catalog, and downstream BI and operational systemsArchitect and implement MLflow-based model lifecycle management (experiment tracking, model registry, versioning, and deployment) across development, staging, and production environmentsEvaluate and recommend AI/ML frameworks, foundation models, vector databases, and GenAI tooling (e.g., LangChain, LlamaIndex, Azure OpenAI, Semantic Kernel) aligned to Primoris' use cases and platform standardsPartner with enterprise architecture, security, and infrastructure teams to ensure AI/ML systems align with broader platform, integration, and compliance standardsLead the end-to-end delivery of AI/ML use cases from requirements and data exploration through model development, validation, deployment, and production monitoringServe as the first point of contact for technical challenges or escalations related to AI/ML workloads in development and production, including triage, root cause analysis, and remediationProvide technical leadership and delivery oversight across hybrid teams including internal engineers, consulting partners, and offshore resources, ensuring clear accountability and consistent outcomesEstablish and champion AI/ML engineering standards (experiment reproducibility, model versioning, CI/CD for ML, automated testing, observability, and incident runbooks) to ensure production-grade deliveryDefine and implement model monitoring frameworks to detect drift, degradation, and anomalies in production AI/ML systems, with appropriate alerting and retraining triggersOne or more Databricks certifications (e.g., Databricks Certified Machine Learning Professional)Experience with vector databases (e.g., Azure AI Search, Pinecone, Weaviate, ChromaDB) and embedding model workflowsFamiliarity with Power BI semantic models and DAX, and ability to collaborate effectively with BI and data modeling teams on AI-enriched reporting solutionsBackground in construction, engineering, or infrastructure industry data and business processesCompany OverviewDice is the go-to career marketplace for tech professionals. It was founded in 2010, and is headquartered in Drachten, Friesland, NLD, with a workforce of 201-500 employees. Its website is https://www.or-quest.nl/.Company H1B SponsorshipDice has a track record of offering H1B sponsorships, with 2 in 2022, 4 in 2021, 5 in 2020. Please note that this does not guarantee sponsorship for this specific role.