Director, GTM AI Engineering

Samsara · Remote - US

  • Senior
  • Full-time
  • $182,000 – $325,000
  • Posted 2026-10-30
  • Confirmed live on 31 October 2026

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Job description

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 Machine Learning, AI, Analytics & Data (MAAD) team builds the intelligence and technology that helps our go-to-market teams work faster, make better decisions, and spend more time with customers.

As the Director, GTM AI Engineering you’ll run our AI Engineering team for GTM. You’ll work closely with Data Science, Analytics, and Data Engineering to serve Sales, Customer Success, Support, Enablement, and GTM leadership. This is a hands-on Director role. Expect to spend about 70% of your time building (prototyping agents, writing code, designing evals) and about 30% leading the team, setting strategy, and influencing stakeholders.

You’ll build intelligent workflow experiences. That ranges from AI agents and copilots that take manual work off sellers’ plates, to signals for propensity and prioritization, to the data, evaluation, and measurement foundations that make these products reliable and trusted.

The ideal candidate is AI-native. You already run your own work through agents every day, you’ve shipped AI products to production, and you get as excited about a seller’s first “wow, this saved me an hour” moment as you do about a clean architecture.

This is a remote position open to candidates residing in the US.

In this role, you will:

• Build hands-on. Prototype, ship, and iterate on AI agents, copilots, and workflow automations for GTM teams, from the first demo to a production system people rely on.

• Build the platform, not just the apps. Own the architecture of the shared GTM AI platform: orchestration, LLM and tool gateways, identity and access, and the MCP and SDK contracts that let the GTM web app, Salesforce, Slack, desktop, and Claude plugins share one set of governed capabilities.

• Make evals a first-class discipline. Design evaluation frameworks for agent and LLM behavior, including golden datasets, LLM-as-judge, human review loops, and regression suites, and run them in development and production. Use transcript analysis and eval results to find failures, guide what to fix first, and show quality improving over time.

• Lead with AI day to day. Use agents, coding assistants, and agent harnesses in your own daily work, and build the shared tooling, patterns, and harnesses that make the whole team faster.

• Stay ahead of the curve. Track new models, agent frameworks, MCP and tool ecosystems, and context engineering, and turn them into practical recommendations for Samsara's GTM use cases: what to adopt, what to test, and what to ignore. Make clear build-versus-buy calls on vendor tools, not just models.

• Drive adoption with the field. Be the go-to advocate for AI across Sales, CS, and Support. Run demos, earn credibility with reps and frontline managers, collect real feedback, and turn skeptics into power users.

• Set the strategy. Own the technical and product strategy for GTM AI, including the data foundations, instrumentation, governance, and observability these products depend on. Decide which prototypes move onto the shared platform, which merge, and which retire. Own model routing across vendors and the per-user spend controls that keep AI cost in line with value. Influence senior leaders on AI priorities, investment, and the operating model.

• Ship revenue-critical intelligence. Own the forecasting, propensity, and CRM data-quality work that sales leadership acts on, and keep it calibrated, validated, and clear about its limits. Be comfortable across data and analytics engineering, and act as a business leader when the work calls for it.

• Partner across GTM, Product, and Engineering. Work with Sales, Customer Success, Support, Enablement, Operations, Product, and Engineering leaders to find high-value opportunities, define success metrics, and turn them into durable products.

• Build for trust. Put a pragmatic responsible-AI approach in place: safety, privacy, reliability, and human-in-the-loop workflows with clear approval and

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