Senior AI Platform Engineer

Samsara Samsara · Enterprise · FL · Remote · Business Systems

Senior AI Platform Engineer to build, ship, and scale Samsara’s Enterprise AI platform, providing end-to-end capabilities for AI agents. The role involves owning the full lifecycle of AI-powered systems, from design and prototyping to production deployment and monitoring. Key responsibilities include architecting and scaling GenAI capabilities, leading investments in RAG, embedding pipelines, LLM orchestration, and multi-modal data processing, and integrating AI solutions with internal and external systems.

What you'd actually do

  1. Build, and own end-to-end Data & AI platform (Databricks,AWS or other tech stack) from ideation , prototyping , production deployment and monitoring.
  2. Architect and scale company-wide GenAI capabilities to support domain-specific business AI Agents that are embedded into real operational workflows.
  3. Provide documentation and support to business users to deploy and manage AI agents at scale.
  4. Lead platform investments in areas like RAG infrastructure, embedding pipelines, LLM orchestration, and multi-modal data processing.
  5. Serve as a technical anchor and mentor for the broader AI & Data team, raising the engineering bar across the organization.

Skills

Required

  • Python
  • AI/ML fundamentals
  • Generative AI solutions
  • LLMs
  • vector databases
  • prompt engineering
  • embeddings
  • RAG systems
  • AI agent development frameworks and tooling (e.g., LangChain, LangGraph, CrewAI, LlamaIndex, OpenAI SDK, MCP, A2A)
  • Databricks
  • AWS
  • software engineering excellence
  • reliability
  • observability
  • maintainability

Nice to have

  • 0→1 MVP development
  • iterative prototyping
  • evolving prototypes into production-grade systems
  • staying up to date with industry news, AI development trends, tools, and best practices
  • SDLC best practices
  • modern AI development tools and patterns
  • cross-functional settings
  • translate business needs into technical solutions

What the JD emphasized

  • own the full lifecycle of AI-powered systems
  • AI agent development frameworks and tooling

Other signals

  • AI Platform Engineering
  • GenAI capabilities
  • AI agents
  • LLM orchestration
  • RAG infrastructure