Who we are
Samsara (NYSE: IOT) is the pioneer of the Connected Operations™ Cloud, which is a platform that enables organizations that depend on physical operations to harness Internet of Things (IoT) data to develop actionable insights and improve their operations. At Samsara, we are helping improve the safety, efficiency and sustainability of the physical operations that power our global economy. Representing more than 40% of global GDP, these industries are the infrastructure of our planet, including agriculture, construction, field services, transportation, and manufacturing — and we are excited to help digitally transform their operations at scale.
Working at Samsara means you’ll help define the future of physical operations and be on a team that’s shaping an exciting array of product solutions, including Video-Based Safety, Vehicle Telematics, Apps and Driver Workflows, and Equipment Monitoring. As part of a recently public company, you’ll have the autonomy and support to make an impact as we build for the long term.
About the role:
Samsara’s Revenue Operations AI & Data Team is building the future of how we go to market — with intelligence, personalization, and speed. We’re a high-impact team of builders, scientists, and strategists focused on transforming sales operations through AI. Our mission is to help sellers reach the right customer at the right time with the right message — and to put everything they need at their fingertips, whether that’s data from Salesforce, context from a past call, or content that wins deals.
As a Senior Software Engineer, AI Platform, you’ll lead the design and development of core platform capabilities that power Samsara’s next generation of AI-driven experiences. You’ll focus on building scalable, reliable systems that enable multi-step AI workflows, model execution, and integrations across products, rather than individual features. This role sits at the intersection of distributed systems and applied AI, where correctness, extensibility, and operational excellence matter as much as speed.
You’ll partner closely with AI engineers, backend engineers, and cross-functional teams to shape shared execution patterns, define platform contracts, and evolve the foundations that support S+Engine and future AI use cases. You’ll be empowered to make architectural decisions, move fast on early iterations, and help turn emerging AI capabilities into a durable, production-grade platform that other teams can build on with confidence.
This is a remote position open to candidates residing in the US except the San Francisco Bay Metro Area, NYC Metro Area, and Washington, D.C. Metro Area.
You should apply if:
- You want to impact the industries that run our world: Your efforts will result in real-world impact—helping to keep the lights on, get food into grocery stores, reduce emissions, and most importantly, ensure workers return home safely.
- You are the architect of your own career: If you put in the work, this role won’t be your last at Samsara. We set up our employees for success and have built a culture that encourages rapid career development, countless opportunities to experiment and master your craft in a hyper growth environment.
- You’re energized by our opportunity: The vision we have to digitize large sectors of the global economy requires your full focus and best efforts to bring forth creative, ambitious ideas for our customers.
- You want to be with the best: At Samsara, we win together, celebrate together and support each other. You will be surrounded by a high-calibre team that will encourage you to do your best.
In this role, you will:
- Build and evolve core AI platform capabilities that enable teams to develop, run, and scale GenAI-powered applications across Samsara.
- Design and implement shared execution patterns, APIs, and services that support multi-step AI workflows and system integrations.
- Develop reliable, extensible backend systems that power AI-driven experiences used across the sales funnel and beyond.
- Work hands-on across the stack, from backend services and execution infrastructure to integration with AI models and tooling.
- Collaborate closely with AI engineers, data scientists, product partners, and sales operators to turn emerging AI use cases into production-ready platform capabilities.
Minimum requirements for the role:
- 6+ years of professional software engineering experience (excluding internships/contract roles) , with a strong emphasis on building and operating large-scale, production backend or platform systems.
- Hands-on experience building and operating GenAI-powered systems in production , including integration with large language models (LLMs) or similar AI services.
- Experience designing or implementing GenAI workflows such as prompt orchestration, tool execution, routing, or multi-step reasoning pipelines.
- Proven experience designing and implementing distributed systems that support multi-step execution, asynchronous workflows, and well-defined service contracts.
- Strong proficiency in backend programming languages (e.G., Python, Java, Go, or similar) and experience building reliable services with clear input/output schemas.
- Expert in Python and GenAI frameworks (e.G., LangChain, OpenAI SDK, MCP, etc.)
- Familiarity with GenAI quality and safety considerations, such as validation of model outputs, structured responses, retries/fallbacks, and basic evaluation or monitoring approaches.
- Strong product sense and ability to work in fast-paced, cross-functional environments.
- Located in and authorized to work in the United States (this is a fully remote role).
An ideal candidate also has:
- Experience working on AI products in a sales, go-to-market, or revenue operations context.
- Familiarity with enterprise tools like Salesforce, Gong, Outreach, or similar CRM/enablement platforms.
- Experience integrating with vector databases, retrieval systems, or streaming voice/chat pipelines.
- A track record of leading major technical initiatives or mentoring engineers in high-growth teams.
- Exposure to infrastructure considerations such as cost optimization, model evaluation, observability, and latency management.