Ideal candidates will have a strong foundation in AI/ML, cloud platforms, and data engineering. They will use these skills as tools for building intelligent systems that support real-world digital operations. This role offers the opportunity to work at the intersection of cloud technologies, AI, and commerce enablement, driving value through scalable insights and automation. We are seeking an AI Engineer to join our growing data and intelligence team. If you enjoy solving complex business problems using advanced AI/ML tools and cloud-native solutions—while working with diverse data from digital commerce, marketing, and content platforms—read on! Role responsibilities Design, build, and scale AI/ML solutions using cloud-native tools across GCP, Azure, and AWS to support use cases like anomaly detection, content classification, predictive KPIs, and intelligent workflow automation. Leverage Databricks to develop unified data pipelines, orchestrate model training/inference workflows, and support real-time decisioning across multiple systems. Collaborate with data analysts, platform engineers, and business stakeholders to operationalize models that drive measurable impact (e.g., SLA improvements, user behavior insights, conversion predictions). Build AI-powered dashboards and explainable insights using Power BI, Tableau, or Looker—enabling business users to make informed decisions backed by models. Apply advanced techniques (e.g., NLP, time series forecasting, clustering) to optimize platform stability, personalization, and operational readiness. Integrate AI solutions with platform telemetry (e.g., observability logs, ticket metadata, content usage stats) to surface proactive insights and reduce downstream escalations. Champion data integrity, reusability, and responsible AI practices across the lifecycle of development, deployment, and monitoring. Establish performance monitoring, alerting, and drift detection mechanisms to ensure model integrity and business alignment post-deployment. Support conversational analytics through GenAI/LLM interfaces for natural-language querying of marketing and commerce data. Architect real-time inferencing capabilities using event-driven tools (e.g., Pub/Sub, Kafka) and integrate with commerce or marketing platforms for next-best-action recommendations. To qualify, candidates should meet all minimum qualifications below. Even if you do not meet all preferred qualifications, we encourage you to apply. 5+ years of experience building and deploying machine learning models in production environments. Proficiency with Databricks and cloud-native ML tooling across GCP (Vertex AI), Azure ML, or AWS SageMaker. Strong programming skills in Python and SQL; experience with frameworks such as scikit-learn, TensorFlow, PyTorch, or MLflow. Experience building data pipelines, training workflows, and model-serving systems in enterprise environments. Experience creating AI-integrated dashboards or tools using Power BI, Tableau, or Looker. Ability to collaborate with cross-functional teams including product owners, analysts, QA, and DevOps. Experience deploying models in GCP, especially with Vertex AI Pipelines, BigQuery ML, and GenAI Studio or similar. Understanding of data product thinking—turning ML insights into reusable APIs, dashboards, or workflows. Hands-on with model explainability, governance, and bias detection tools (e.g., What-If Tool, SHAP, Model Cards). Preferred qualifications Exposure to multi-platform digital ecosystems (e.g., commerce platforms, content management, observability tooling, customer data platforms). Familiarity with orchestration tools like Airflow or event-based workflows using Pub/Sub, Kafka, or Event Grid. Experience integrating ML models into monitoring systems or observability stacks (e.g., ELK, Prometheus, Grafana). Understanding of data governance and MLOps best practices (e.g., drift detection, version control, explainability). Strong communication skills to translate technical findings into business narratives. Previous experience contributing to AI strategy and solution architecture in enterprise settings. Experience with LLM/GenAI, especially for insights extraction and conversational UX. Experience in retail or multi-brand global ecosystems. Worked in environments requiring cross-platform telemetry aggregation—logs, content stats, error traces, SLA metadata, etc. Experience with multi-region data architectures and compliance-aware ML deployment. Your process After applying, you will be contacted if your skills and experience match. Be cautious of recruitment fraud—only engage with email contacts ending with '@valtech.com' or '@kinandcarta.com'. We support inclusive hiring and reasonable adjustments. Contact us at [email protected] if needed. About Valtech Valtech is an experience innovation company that helps brands unlock value through data, AI, creativity, and technology. Our global team of 6,500 professionals in over 60 offices work with organizations like L’Oreal, NatWest, DWP, P&G, Volkswagen, and the US Department of Agriculture. We are committed to creating an equitable workplace where everyone can thrive and grow. At Valtech, we believe in transforming through action, not just words. #J-18808-Ljbffr