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.
Nice to Have
- 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.