Sr. Software Engineer Ii, AI Platform

Samsara Samsara · Enterprise · Atlanta - ATL2, - AR, - Dallas · Remote · Revenue Operations

Senior Software Engineer, AI Platform role focused on building core platform capabilities for GenAI-powered applications. This involves designing and implementing scalable, reliable systems for multi-step AI workflows, model execution, and integrations. The role sits at the intersection of distributed systems and applied AI, requiring hands-on experience with backend services, execution infrastructure, and AI model integration, with a focus on creating a production-grade platform for other teams.

What you'd actually do

  1. Build and evolve core AI platform capabilities that enable teams to develop, run, and scale GenAI-powered applications across Samsara.
  2. Design and implement shared execution patterns, APIs, and services that support multi-step AI workflows and system integrations.
  3. Develop reliable, extensible backend systems that power AI-driven experiences used across the sales funnel and beyond.
  4. Work hands-on across the stack, from backend services and execution infrastructure to integration with AI models and tooling.
  5. Collaborate closely with AI engineers, data scientists, product partners, and sales operators to turn emerging AI use cases into production-ready platform capabilities.

Skills

Required

  • 6+ years of professional software engineering experience
  • building and operating large-scale, production backend or platform systems
  • building and operating GenAI-powered systems in production
  • integration with large language models (LLMs) or similar AI services
  • designing or implementing GenAI workflows
  • prompt orchestration
  • tool execution
  • routing
  • multi-step reasoning pipelines
  • designing and implementing distributed systems
  • multi-step execution
  • asynchronous workflows
  • well-defined service contracts
  • Python
  • Java
  • Go
  • building reliable services with clear input/output schemas
  • LangChain
  • OpenAI SDK
  • MCP
  • validation of model outputs
  • structured responses
  • retries/fallbacks
  • basic evaluation or monitoring approaches
  • Strong product sense
  • working in fast-paced, cross-functional environments

Nice to have

  • AI products in a sales, go-to-market, or revenue operations context
  • Salesforce
  • Gong
  • Outreach
  • CRM/enablement platforms
  • vector databases
  • retrieval-augmented generation (RAG)
  • model serving infrastructure
  • GPU kernels
  • quantization

What the JD emphasized

  • building and operating large-scale, production backend or platform systems
  • building and operating GenAI-powered systems in production
  • designing or implementing GenAI workflows
  • designing and implementing distributed systems

Other signals

  • building core AI platform capabilities
  • multi-step AI workflows
  • integrations across products
  • distributed systems and applied AI
  • production-grade platform