Senior Manager, Software Engineering

Walmart Walmart · Retail · Bentonville, AR

Senior Manager, Software Engineering to lead the design and delivery of scalable platform capabilities, integrating AI/ML technologies to enhance engineering productivity and system resilience. The role involves managing a team, driving technical vision, and owning end-to-end ML infrastructure including data pipelines, feature engineering, model serving, and evaluation systems.

What you'd actually do

  1. Technical Leadership: Drive the technical vision and strategy for the engineering team. Driving team towards AI first mindset. Stay current with cutting-edge technologies and best practices in software engineering.
  2. Business Acumen and Strategic Planning: Comprehend the business context of the work, make informed decisions that align with the overall leadership vision and strategy and identify opportunities to leverage technology to drive business outcomes.
  3. Team Management: Manage a team of highly skilled engineers. Foster a positive, inclusive, and collaborative work environment. Facilitate team meetings, code reviews, and knowledge sharing sessions.
  4. Project Management: Coordinate with cross-functional teams to ensure projects are delivered on time and within budget. Monitor project progress, manage risks, and ensure high standards of quality.
  5. Mentorship: Provide guidance and mentorship to team members. Promote continuous learning and professional development within the team.

Skills

Required

  • 14+ years of relevant experience
  • Minimum of 5 years of experience with agile principles and practices
  • Experience in leading Scrum teams
  • Hands on experience in building scalable cloud native software platforms/applications
  • Very strong understanding and experience in software development lifecycle
  • Strong Java/J2EE, React native skill or any other front end experience
  • Strong understanding of architecture, database, messaging (Kafka services)
  • SQL/Cosmos/Cassandra/Azure database proficiency

Nice to have

  • Hands-on experience with developer platforms is a strong advantage

What the JD emphasized

  • Own end-to-end ML infrastructure including parsers/stitchers for omni-channel data, multi-tenant data pipelines, feature engineering platforms, model serving infrastructure, evaluation systems (including site crawling, query sampling, NDCG evaluation), and experimentation frameworks

Other signals

  • leading ML infrastructure
  • data pipelines
  • feature engineering
  • model serving
  • evaluation systems