Software Engineer

Overview

Design, build, and operate scalable software and machine learning solutions that enable Data & AI-driven products for Lowe's Demand Forecasting team (LIFT), working across the full Software Development Lifecycle.

What you'll do

• Design, develop, test, deploy, and support scalable, secure, and maintainable software and ML solutions, including backend services, APIs, cloud-native applications, data integrations, and ML-enabled services supporting Forecasting and AI products.
• Translate business and functional requirements into technical designs and high-quality implementations, contributing across the full Software Development Lifecycle (SDLC).
• Build and maintain data ingestion, transformation, preprocessing, feature engineering, and post-processing pipelines to support ML model training, experimentation, and inference.
• Partner with Data Scientists and Data Engineers to translate model requirements into production-ready engineering solutions and ensure high-quality, reliable data is available for model development and execution.
• Support the end-to-end ML lifecycle, including experimentation, model registration and versioning, testing, deployment, orchestration, inference, and ongoing model management using enterprise AI/ML platforms.
• Develop and maintain CI/CD and automation pipelines for software, data pipelines, and ML models to enable reliable and repeatable testing and deployments.
• Implement monitoring and observability for applications, data pipelines, and ML models, including system health, data quality, model performance and drift, and operational metrics.
• Optimize software, ML workloads, and data pipelines for performance, scalability, reliability, and cost efficiency across cloud and enterprise platforms.
• Apply engineering best practices including secure coding, code reviews, automated testing, documentation, performance optimization, data governance, security, and compliance.
• Support production systems through monitoring, incident resolution, root-cause analysis, troubleshooting, and continuous reliability improvements.
• Collaborate with Product, Data Science, Data Engineering, Architecture, Security, Infrastructure, and business teams to deliver reliable Forecasting and AI capabilities that support business decision-making.
• Participate in technical design discussions and code reviews, contribute to engineering standards, share knowledge with team members, and evaluate modern technologies, AI-enabled development tools, and automation to continuously improve software quality and engineering productivity.

What you'll need

• Bachelor's degree in computer science, computer information systems, or related field, or equivalent years of experience in lieu of education requirement, if applicable.
• 2 years of experience in software development or a related field.
• 2 years of experience working on project(s) involving the implementation of solutions applying development life cycles (SDLC) through iterative agile development.
• 2 years experience working with any of the following: frontend technologies (user interface/user experience), middleware (microservices and application programming interfaces), database technologies, or DevOps.
• Minimum 2 years of experience in applications powered by AI/ML with large dataset and Data Engineering.
• Hands-on experience (real-time) and proficiency in building robust, reliable and scalable data/ML pipelines for Analytics and AI/ML systems, working with large sets of structured and unstructured data from disparate sources.
• MLOps tools and frameworks 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 systems: Hadoop Ecosystem (HDFS, Hive, MapReduce) or Cloud Analytics database like Druid; data visualisation/exploration tools like Superset.
• CI/CD.
• Git.

Nice to have

• Master's degree in computer science, CIS, or related field.
• 2 years of experience writing technical documentation in a software environment and developing and implementing business systems within an organization.
• Apache Airflow, Cloud Composer.
• GCP cloud experience, BigQuery.
• 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.

Details

• Location: Bengaluru, India, on-site office.