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Salary: USD 113,645 - 191,000 / annual
Samsara (NYSE: IOT) is the pioneer of the Connected Operations Cloud, a platform that enables organizations in agriculture, construction, field services, transportation, and manufacturing to harness IoT data for actionable insights and operational improvement.
The Safety Engineering - Triage & Insights Team owns and builds systems and customer-facing products across web, mobile, and API surfaces that help fleets identify unsafe driving behaviors and recognize positive driving habits. The team ingests sensor and media data, detects risky behaviors, and serves as the source of truth for safety events—from automations and safety inboxes to reports, safety scores, and driver coaching.
The team is building the next generation of safety products to be AI-native, developing LLM-powered workflows, agentic systems, and conversational experiences that help customers move from manual incident review and reactive coaching toward proactive, intelligent, and self-serve safety operations. This includes AI-driven driver experiences that go beyond static reports into live, two-way interaction, and agent-assisted tools that let safety managers triage and act on their data.
As a Software Engineer II, you will own customer-facing features from concept to production. You will partner closely with Product, Design, and ML/AI engineering teams to evolve products, refine workflows based on customer input, and deliver scalable, AI-powered solutions. Key responsibilities include:
- Own customer-facing features and platform capabilities end-to-end, from design and implementation through rollout and production, including taking AI prototypes to production at scale.
- Architect, build, test, and deliver full-stack products across reliable services, APIs, and web and mobile experiences using technologies such as Golang, GraphQL, TypeScript, React, React Native, and MySQL.
- Build AI-native product experiences: integrate LLMs into safety workflows, develop agent tooling and retrieval-augmented generation (RAG), and design interactions between AI agents and the product UI.
- Design and run evaluations and build human-in-the-loop feedback loops that continuously improve accuracy, precision, and reliability of insights.
- Use AI coding tools and agents in your own workflow to plan, build, and ship faster.
- Make thoughtful technical tradeoffs across speed, maintainability, scalability, cost, and customer impact.
- Own the operational health of production systems, improving reliability and scalability as the customer base grows.
- Collaborate across Engineering, Product, Design, ML, and platform teams to deliver cohesive customer experiences.
- Champion and embed Samsara's cultural principles as the company scales globally.
REQUIREMENTS:
- 3+ years of professional software engineering experience building, shipping, and operating reliable customer-facing production systems.
- Strong programming fundamentals in a language such as Golang, Java, or Python, with experience writing clean, maintainable code and reviewing peers' code.
- Experience developing features or end-to-end solutions across backend services, APIs, and modern web applications.
- Experience or demonstrated interest in AI-native development, including integrating LLMs into products, building agentic workflows, or running evaluations to improve AI-generated output quality.
- Experience using data, metrics, logs, tests, or tracing to investigate issues, validate releases, and improve reliability.
- Ability to independently own moderately complex projects, with the ability to estimate, communicate, and deliver on milestones.
- Strong communication and collaboration skills across engineering and cross-functional partners.
- A growth mindset, strong product intuition, and excitement for learning new technologies and building impactful customer experiences.
IDEAL CANDIDATE ALSO HAS:
- Experience building and scaling customer-facing AI or LLM-powered products in production, including agent tooling, RAG, prompt engineering, or conversational and voice experiences.
- Experience with LLM evaluation and observability tools such as Langfuse or Eino, and optimizing LLM-powered systems for cost and token efficiency.
- A track record of using AI coding agents to plan and deliver features, not just autocomplete.
- Experience working across the stack with modern technologies such as Go, GraphQL, TypeScript, React, React Native, and AWS (or Azure or Google Cloud).
- Familiarity with observability, rollout practices, and monitoring approaches that improve product reliability and operational excellence.
- Experience operating in fast-paced, highly collaborative environments with distributed teams.
- Bachelor's degree in Computer Science, Engineering, or a related field.
