Description
We are seeking a Digital Customer Success Manager, AI & Automation to be a hands-on developer responsible for designing, testing, deploying, and maintaining agentic systems to support a digital-first post-sales strategy.
Key responsibilities include:
- Customer Journey Optimization: Pinpoint friction points in the customer experience, create proactive interventions, and turn interactions into automated, personalized journeys.
- End-to-End Execution: Write code, execute experimental tests, and continuously maintain production solutions.
- Cross-Functional Alignment: Partner across teams to ensure a cohesive experience for all users.
Success is measured by key customer outcome metrics, including increased adoption, minimized churn risk, and higher NRR tied to the agents you deploy.
You will:
- Analyze: Identify customer painpoints and areas of opportunity with an analytical mindset combined with a customer-centric lens.
- Build: Build the digital CS playbooks, taking advantage of the programs and resources other teams have built, design agent architectures, write prompts, integrate with external systems (Salesforce, Samsara platform, Customer Success tools), build guardrails, and write clean Python code that the team can maintain.
- Test: Define success criteria and evaluation frameworks before you write the first line of code. Build automated test suites that cover real-world scenarios, edge cases, and known failure modes.
- Deploy: Own the deployment, versioning, and rollback plan for every agent. Ensure agents are production-ready before they reach CSMs. Ensure anything we deploy makes the experience more simple, not more complex, for our customers.
- Monitor: Track agent performance in production , monitor accuracy, latency, failure rates, and customer outcomes. Detect drift before anyone has to tell you something's wrong.
- Maintain & Iterate: Update agents continuously as Samsara's product evolves, Customer Success playbooks change, and real-world data indicates what needs improvement.
Minimum requirements for the role:
- Hands-on experience building and maintaining production LLM-based agents or automations, with at least 1 year working directly with LLMs or AI agents in production
- Ability to code rapidly with Python proficiency or skilled at using AI to code; have a track record of connecting AI to external systems: CRMs, APIs, customer data, and operational tools
- Experience using product usage data to spot risk and opportunity (health signals, activation milestones, usage floors) and acting on it before it surfaces in a renewal conversation
- Comfort running experiments and drawing sound conclusions from the data in order to improve the performance
- A systems mindset for managing a high-volume book of business: you build repeatable playbooks and motions, not just manage individual relationships
- 3+ years of experience, preferably in a B2B SaaS environment
The compensation range for this role is $105,910-$160,200 USD per year.