AI Engineering Manager

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 youll help define the future of physical operations and be on a team thats 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 youll have the autonomy and support to make an impact as we build for the long term.

ABOUT THE ROLE

Samsaras Go-To-Market Systems team is building the AI-first infrastructure that powers how one of the worlds fastest-growing SaaS companies sells. As Engineering Manager GTM AI Engineering youll lead a team of senior engineers who build and operate the AI orchestration engines Salesforce/CRM/PRM integrations and agentic workflows that keep our global sales organization moving.

This role is for a hands-on engineering leader someone who writes code conducts design reviews and shapes architecture alongside the team while also owning the people processes that make a great team great: hiring career development performance and culture. Youll partner closely with Sales Ops BizTech Finance and GTM leadership to translate business ambitions into reliable scalable engineering roadmaps.

Youll report to the Sr. Director Sales Technology Engineering and serve as the technical and people lead for a team of 47 engineers. Youll set the standard for code quality architectural thinking on-call discipline and how the team shows up in cross-functional conversations.

YOU SHOULD APPLY IF

• You thrive at the intersection of hands-on technical leadership and people management youre equally comfortable in a design review and a 1:1 conversation about career growth
• You believe great managers unblock their teams by being technically credible not by staying out of the code
• Youve built and shipped production AI systems and know what it takes to take an agentic workflow from prototype to enterprise reliability
• Youre energized by ambiguity you can take a fuzzy business need from a VP of Sales and turn it into a concrete engineering roadmap
• You care about building an inclusive high-trust team where engineers grow and do the best work of their careers

IN THIS ROLE YOU WILL

• Lead hire and develop a team of 47 senior engineers across the full GTM AI systems stack setting a high bar for technical excellence collaboration and delivery
• Stay hands-on: contribute to system architecture participate in code and design reviews pair with engineers on complex problems and own critical technical decisions for the teams most impactful systems
• Own the engineering roadmap for GTM AI systems partnering with Sales Ops BizTech Finance Legal and GTM leadership to set priorities define milestones and communicate progress
• Drive delivery of AI-first GTM systems: agentic AI pipelines LLM orchestration layers Salesforce CPQ integrations real-time Slack applications and AWS event-driven architectures
• Champion engineering quality: establish and uphold standards for code review testing observability (distributed tracing alerting SLAs) incident response and documentation
• Create a culture of responsible AI development ensuring the team follows safe data handling practices maintains audit trails and builds human-in-the-loop controls from the start
• Manage team health: run effective 1:1s give timely and actionable feedback unblock engineers resolve conflicts and advocate for your teams needs within the broader org
• Identify and eliminate systemic sources of friction in GTM workflows turning recurring manual processes into automated self-healing systems that scale with the business
• Serve as a technical authority in cross-functional conversations representing the engineering teams perspective to VP- and C-level GTM stakeholders

MINIMUM REQUIREMENTS

• 8 years of software engineering experience including 2 years in an engineering management or tech lead role with direct reports
• Strong technical depth in Python (production services async processing LLM integration) and TypeScript/JavaScript (React )
• Hands-on Salesforce platform experience: REST/Bulk/Streaming APIs SOQL CPQ/Steelbrick platform events and flow automation
• Solid AWS expertise: Lambda SQS/SNS/EventBridge API Gateway S3 RDS/Aurora CloudWatch IAM and multi-account patterns
• Experience building and deploying LLM-powered systems using OpenAI API Anthropic API LangChain LangGraph or equivalent agentic frameworks
• Demonstrated ability to lead multi-engineer technical efforts: writing design docs running design reviews and defining engineering standards
• Track record of effective people management: hiring performance development and building inclusive team culture
• Strong cross-functional communication skills able to translate engineering decisions to non-technical business stakeholders
• Bachelors degree in Computer Science Engineering or related field or equivalent practical experience

AN IDEAL CANDIDATE ALSO HAS

• Experience designing and operating low-code automation platforms (Workato MuleSoft Salesforce Flow) alongside custom-built agentic systems
• Background in GTM engineering RevOps tooling or sales technology platform development in a high-growth B2B SaaS environment
• Familiarity with Model Context Protocol (MCP) or custom tool/function-calling patterns in production agentic systems
• AWS certifications: Solutions Architect Professional or DevOps Engineer Professional
• Experience operating in GovRAMP or FedRAMP-adjacent environments
• Prior experience scaling an engineering team through a period of significant organizational or technical growth

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