careers.homedepot.com
Software Engineer Manager, AI/ML Platforms
Location
United States
Posted
4 days ago
Salary
$140K - $240K / year
Seniority
Lead
Job Description
Software Engineer Manager, AI/ML Platforms
The Home Depot
• Collaborates and pairs with product team members (UX, engineering, and product management) to create secure, reliable, scalable software solutions • Documents, reviews and ensures that all quality and change control standards are met • Writes custom code or scripts to automate infrastructure, monitoring services, and test cases • Works with vendors and partners for the successful implementation of critical tooling and platforms • Creates meaningful dashboards, logging, alerting, and responses to ensure that issues are captured and addressed proactively • Contributes to enterprise-wide tools to drive destructive testing, automation, and engineering empowerment • Evaluates new technologies for adoption across the enterprise • Participates in and leads review board sessions to drive consistency across the enterprise • Fields questions from engineers, product teams, or support teams • Monitors tools and participates in conversations to encourage collaboration across product teams • Provides application support for software running in production • Acts as a technical escalation point for the engineers on the team • Provides leadership, mentoring, and coaching to Software Engineers • Attracts, retains, and develops top talent to build a world class Software Engineering Team • Conducts annual and mid-year reviews by reviewing individual development plans and team feedback • Fosters collaboration with team members to drive consistency across product teams, and finds opportunities to expose engineers to career interests • Acts as a proponent of modern software development practices • Guides team members in strategy, alignment, analysis, and execution tasks within and across product teams • Participates in and contributes to learning activities around modern software design and development core practices (communities of practice) • Learns, through reading, tutorials, and videos, new technologies and best practices being used within other technology organizations • Builds relationships with technology leaders at other companies to learn best practices and elegant solutions to common problems
Job Requirements
- 7-9 years of relevant work experience
- Mastery of a modern programming language (preferably Java & Python)
- Experience building, productionizing, and operating AI/ML systems, statistical models, recommendation systems, personalization platforms, or Generative AI solutions at enterprise scale
- Hands-on experience with big data platforms, distributed data processing, and large-scale data pipelines
- Experience with orchestration and workflow tools such as Apache Airflow, Cloud Composer, or similar platforms
- Experience with MLOps practices, including model deployment, monitoring, retraining workflows, feature pipelines, experimentation, and production model governance
- Experience working with cloud platforms, preferably Google Cloud Platform, including services such as BigQuery, Vertex AI, Dataflow, Dataproc, Pub/Sub, Cloud Storage, and Kubernetes
- Experience designing and scaling high-throughput, low-latency, distributed systems that support customer-facing recommendations, search, personalization use cases
- Strong SQL skills and experience working with relational, NoSQL, and analytical data stores
- Experience integrating AI/ML models into production applications, APIs, data products, or decisioning platforms
- Experience with experimentation platforms, A/B testing, feature evaluation, ranking systems, or optimization techniques
- Experience with retail, ecommerce, search, personalization, or recommendation platforms preferred
- Experience using AI agents or developer productivity tools to improve engineering effectiveness, accelerate delivery, and raise team quality
- Strong understanding of modern software delivery practices, CI/CD pipelines, observability, automated testing, and production readiness
- Proficient in troubleshooting complex distributed systems, analyzing logs, monitoring system health, and resolving production issues
- Ability to quickly understand complex systems, identify technical risks, and guide teams toward practical solutions
- Experience mentoring engineers, growing technical talent, and reinforcing strong software engineering fundamentals
- Experience managing team execution, balancing workloads, setting priorities, and delivering through ambiguity
- Experience working across product, data science, analytics, architecture, infrastructure, and business stakeholders in a matrixed environment
- Experience translating high-level strategy into technical roadmaps, delivery plans, and measurable outcomes
- Experience managing vendor relationships, third-party platforms, or external technology partners when needed.
Benefits
- Health insurance
- 401(k) matching
- Paid time off
- Remote work options
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