Sr Software Engineer - AI

The Role

The primary goal is to generate AI/ML forecasts that help the business plan for future demand, optimize resources, reduce risk, and make data-driven decisions.

Work with a Winning Team

As part of a Fortune 50 company and retail leader, your work can change an entire industry. Our CEO is a forward-thinker when it comes to tech, and with one of Forbes Top 50 CIOs leading the charge, you can come to work knowing you’ll have access to the data, tools, and support that few other companies can offer. We also know what it takes to create an inclusive culture that supports you. Our teams are structured around the engineer, giving you the support you need to do your best work.

What You Will Do

• Build and maintain scalable data ingestion, transformation, feature engineering, and post-processing pipelines to support model training, inference, analytics, and reporting.
• Collaborate with Data Scientists, Product, and Business teams to translate business requirements into scalable AI/ML solutions and production-ready data pipelines.
• Design, develop, deploy, and maintain end-to-end ML systems, including model packaging, registration, versioning, deployment, and serving using platforms such as MLflow, Vertex AI, Kubeflow, or similar MLOps tools.
• Build and optimize batch and real-time inference pipelines for performance, scalability, reliability, and cost efficiency across cloud and on-premises environments.
• Implement and maintain CI/CD pipelines and workflow orchestration for AI/ML models and data pipelines using DevOps and MLOps best practices.
• Design and implement monitoring frameworks to track model performance, data quality, data drift, model drift, and production system health.
• Build reusable libraries, utilities, and platform components that improve engineering productivity and standardize ML development across teams.
• Develop production-quality software components following software engineering best practices, ensuring solutions are scalable, testable, maintainable, and efficient.
• Perform root cause analysis, troubleshoot production issues, and participate in code reviews to improve code quality, reliability, and operational excellence.
• Ensure AI/ML solutions comply with security, governance, privacy, and organizational standards throughout the development lifecycle.
• Champion engineering best practices to continuously improve the reliability, scalability, maintainability, and operational efficiency of AI/ML platforms and pipelines.
• Design and implement advanced ML infrastructure patterns, including feature stores, model registries, and automated model lifecycle workflows to enable faster and more reliable AI/ML delivery.
• Partner with engineering and architecture teams to evaluate emerging AI/ML technologies, optimize system architectures, and drive continuous improvements in scalability, performance, and operational maturity.

Required Skills

• Apache Airflow, Cloud Composer, GCP cloud experience, Big Query, Trino/Presto.
• Experience working on Data Quality/Integrity theme, Tools like Great Expectations.
• Domain experience on retail forecasting or any other business forecast predictions/time series forecasting.

Preferred Skills

• Bachelor’s degree in computer science, computer information systems (CIS), or related field or equivalent years of experience in lieu of education requirement, if applicable.
• 5 years of experience in software development or a related field.
• 4 years of experience in any of following competencies: frontend technologies (user interface/user experience), middleware (microservices and application programming interfaces), database technologies, or DevOps.
• 4 years of experience working on project(s) involving the implementation of solutions applying development life cycles (SDLC) through iterative agile development.
• Master’s degree in computer science, CIS, or related field.
• 5+ years of experience developing software, data platforms, or AI/ML applications, including significant experience building and deploying production ML systems.
• Experience leading technical design, implementation, and delivery of ML engineering projects.
• Experience designing, deploying, and operating production-scale ML systems, including live/batch inference, model versioning, monitoring, and lifecycle management.
• Strong understanding of ML platform engineering, automation, and optimizing ML infrastructure for scalability, reliability, latency, and cost efficiency.
• Ability to evaluate infrastructure tradeoffs and recommend effective solutions for ML deployment and operational workflows.
• MLOps tools such as MLflow, Kubeflow, or Vertex AI.
• Foundational understanding of ML models.
• Strong understanding of cloud platforms (GCP, AWS, or Azure).
• Experience managing model registry and implementing versioning best practices.
• Model serving frameworks, SQL, Python, PySpark, Big Data technologies (Hadoop ecosystem or cloud-native equivalents), Analytics databases (Druid), visualization tools (Superset), CI/CD and Git.

Benefits

• 401k with up to 4.25% match.
• Discounted Employee Stock Purchase Plan (15% discount of strike price).
• Tuition-Free Education.
• 10-week Maternity/Parental Leave.
• 10% Associate Discount.

About Lowe’s

Lowe’s Companies, Inc. (NYSE: LOW) is a FORTUNE® 100 home improvement company with total fiscal 2025 sales of more than $86 billion. Lowe’s employs approximately 300,000 associates and operates over 1,750 home improvement stores, 540 branches and 120 distribution centers. Based in Mooresville, N.C., Lowe’s supports the communities it serves through programs focused on creating safe, affordable housing, improving community spaces, helping to develop the next generation of skilled trade experts and providing disaster relief to communities in need.

Pay Range

$95,100.00 - $180,700.00 annually