Manager, AI Platform Engineering , Agent Platform Organization

Amazon Amazon · Big Tech · CA, ON +1 · Data Science

Manager of AI Platform Engineering to lead a team building and operating data pipelines, models, and platform infrastructure for analytics, science, and AI initiatives. The role involves owning delivery and operational health, mentoring a team, and evolving self-service offerings towards agent-driven approaches. The team will build multi-agent solutions to automate data engineering and BI tasks, and develop/deploy agents for analytics use cases like monitoring and anomaly detection. Collaboration with business intelligence, applied science, and product teams is key.

What you'd actually do

  1. lead a team of AI platform engineers building and operating the data pipelines, models, and platform infrastructure that power core analytics, science and AI intatives
  2. own the delivery and operational health of multiple business domains, build and mentor a high-performing team, and help evolve our self-service offerings from reactive dashboards to proactive agent driven approaches
  3. guide this evolution, helping your engineers develop fluency with agentic tooling while maintaining the data engineering fundamentals that everything depends on
  4. help your engineers develop and deploy agents, that solve common Analytics use cases around monitoring, anomaly detection, and insight generation
  5. partner with business intelligence, applied science, and product teams to translate data needs into technical roadmaps, and contribute to shared platform infrastructure when the work calls for it

Skills

Required

  • 3+ years of engineering team management experience
  • Knowledge of engineering practices and patterns for the full software/hardware/networks development life cycle, including coding standards, code reviews, source control management, build processes, testing, certification, and livesite operations
  • Experience working with technical and product stakeholders to define requirements, prioritize features, and influence product roadmaps
  • 7+ years of working directly within data engineering or closely related teams, with hands-on contribution to data platform and pipeline delivery
  • 3+ years of designing or architecting data systems, including data modeling, pipeline patterns, reliability, and scaling strategies
  • 5+ years of experience building or leading development of data pipelines and cloud-native data infrastructure (e.g., data warehouses, data lakes, event-driven architectures, orchestration platforms)

Nice to have

  • Experience leading teams that use generative AI tools and AI development IDEs to accelerate engineering work
  • Familiarity with multi-agent solutions that automate workflows (e.g. pipeline generation, data quality, testing, operational response)
  • Familiarity with at least one agentic AI development IDE (e.g. Kiro, Cursor, Claude Code, Codex)
  • Experience building or overseeing shared data models, semantic layers, or data contracts
  • Familiarity with data governance, cataloging, or lineage tracking practices
  • Experience contributing to or overseeing shared platform infrastructure, developer tooling, or self-service data services
  • Familiarity with observability tooling for data pipelines and data platform operations

What the JD emphasized

  • building and operating the data pipelines, models, and platform infrastructure
  • build multi-agent solutions
  • develop and deploy agents

Other signals

  • leading teams building multi-agent solutions
  • automating data engineering and BI tasks with agents
  • developing and deploying agents for analytics use cases