Senior AI Data Engineer

Samsara is the pioneer of the Connected Operations Cloud, helping organizations that depend on physical operations use IoT data to improve safety, efficiency, and sustainability. The Senior AI Data Engineer will build and operate production AI systems, architect marketing data infrastructure and customer data platforms, automate workflows, and deliver reliable data products while partnering with technical and business stakeholders.

Responsibilities:

• Design, build, and operate production AI systems, including agent orchestration, tool and API integrations, retrieval pipelines, and the evaluation harnesses that keep them reliable and trustworthy
• Architect and maintain marketing databases, datasets, pipelines, and Samsara's Customer Data Platform (CDP) to enable advanced segmentation, targeting, automation, and analytics
• Partner with the BI team to expand conversational analytics across the marketing organization
• Identify and automate manual workflows with AI, taking ideas from concept to prototype to a credible path to production, and delivering efficiency gains across marketing and go-to-market teams
• Stand up new data pipelines end to end, often for a tool that was onboarded yesterday: discovering the schema, working with partners inside Samsara and at the vendor, getting the data processed, and integrating it into our downstream systems
• Own the reliability and data quality of what you build
• Autonomously partner with technical and non-technical stakeholders (Marketing, Sales, R&D, and more) to translate ambiguous business questions into technical requirements and scalable solutions, without dedicated PM support
• Ship high-quality Python and SQL, increasingly by directing agentic coding tools, while holding a high bar for reviewing and verifying AI-generated work before it reaches production
• Mentor engineers, conduct code reviews, and help define best practices for the team

Requirements:

• 5+ years of working experience in a data engineering or AI engineering role, including meaningful hands-on data engineering experience
• Expert Python and SQL knowledge with strong hands-on data modeling experience
• You have built and shipped systems that use LLMs or agents in production as part of your job
• Agentic coding tools (e.g., Claude Code, Cursor) are part of your regular workflow. You actively seek out new ways to use AI to accelerate your work, and you verify and take ownership of AI-generated output
• Deep experience with data warehouse architectures, ETL/ELT, and the modern data stack (e.g., Databricks, DBT, Snowflake, BigQuery, or similar)
• Demonstrated ability to lead requirements gathering independently, bridging the gap between business needs and technical implementation, and to spot opportunities for automation through exploratory conversations with stakeholders
• A self-starter who performs well independently and as a team member, with strong communication and project management skills across technical and non-technical audiences
• A software engineering background beyond data or AI engineering, and a track record of taking ambiguous, unfamiliar problems and turning them into well-architected, delivered solutions
• Experience directly supporting a business function such as marketing, sales, finance, or business operations
• Experience working with Databricks
• Familiarity with go-to-market data and systems: CRM (e.g., Salesforce), marketing automation, web analytics, and CDPs (e.g., Hightouch, Segment)
• Experience evaluating and monitoring LLM systems in production