Customer Support Engineer

Rillet•San Francisco, CA

2d•Hybrid

About The Position

Rillet serves accounting and finance teams with an AI-native ERP designed for speed, accuracy, and insight, enabling a zero-day close. The company offers a unified data model, numerous integrations, automated workflows, and specialized AI agents. Rillet has secured $100M in funding from prominent investors to capture a significant market opportunity. The company culture emphasizes extreme speed, agency, and flexibility, with employees expected to be proactive and customer-focused. This role is for someone who appreciates the value of financial tools and enjoys empowering fast-growing companies.

Requirements

6 months to 3 years in a customer-facing or technical support role (support, success, support engineering, or similar), ideally with exposure to building tools or automations.
Customer-first orientation.
Technically capable and systems-oriented; comfortable scripting, building integrations, and working with APIs, data pipelines, or AI/LLM-powered workflows.
Strong written communication skills in async channels.
Fast learner able to absorb product complexity quickly.
Strong triage instinct to quickly assess and route issues.
Natural ability for pattern recognition and documentation, turning repeated questions into scalable knowledge base content and automation.
Ability to translate vague problems into concrete technical solutions with a bias toward ownership, autonomy, and fast iteration.
High attention to detail in a fast-moving environment.

Nice To Haves

Experience building or integrating AI/LLM-powered workflows in production.
Familiarity with accounting concepts or finance workflows, or previous experience with an accounting-adjacent product.
Experience with Pylon, Linear, or similar CS/support tooling.
Experience at early-stage or fast-scaling startups.

Responsibilities

Resolve inbound support tickets across question types (general knowledge, bug triage, data requests) via omni-channel support, communicating clearly and professionally in async channels.
Triage and escalate issues to Customer Success or Engineering with sufficient context for seamless handoff, and identify gaps in playbooks and escalation protocols.
Build AI-assisted workflows to automate manual support processes such as ticket categorization, response drafting, knowledge retrieval, routing, and enrichment.
Develop internal tools and integrations to scale support execution, connecting support tooling (e.g., Pylon, Linear), the product, and the data warehouse.
Contribute to and continuously improve the internal knowledge base by documenting resolutions, product behavior, and edge cases, and transforming repeated questions into structured content for humans and AI agents.
Tag and categorize tickets consistently to support data quality and AI agent optimization, and instrument support systems with observability.
Take support-infrastructure projects from inception to completion, prototyping quickly and hardening successful systems.
Partner with leadership, Product, and Engineering to identify patterns in customer questions and translate them into product and process improvements.