Senior Customer Success Engineer

About the role

We're hiring a Senior Customer Success Engineer to design and ship AI agents, automations, and internal tools to make our Customer Success team dramatically more effective through the power of AI.

Responsibilities

• Design, build, and iterate on AI agents and applications — both internal tools that automate workflows for the Customer Success team and customer-facing experiences that optimize key moments in the journey (onboarding, self-service support, proactive engagement).
• Scope and prioritize what to build — look at a messy list of requests and identify the highest-leverage opportunity rather than just building what's asked.
• Think from the customer's perspective first — whether building internal tools or customer-facing experiences, consider how real people will interact with what you build and iterate based on their feedback.
• Define success before shipping — set clear metrics, track adoption and outcomes, and use data to validate whether a tool is actually moving the needle.
• Understand the business context behind the work — reason about cost-to-serve, efficiency tradeoffs, and ROI, and use that lens to make better decisions about what to build and how.
• Own the technical decisions end-to-end — select the right LLMs, orchestration frameworks, and third-party tools for each use case, and write clean, maintainable code (leveraging AI-assisted development) that ships quickly without sacrificing reliability.
• Partner with DevOps and Security to ensure AI agents and applications are deployed reliably, meet security and compliance standards, and are built with production-grade infrastructure.
• Collaborate closely with CS leadership and frontline team members to deeply understand pain points and translate them into high-impact solutions.
• Drive adoption and scalability — run demos and training sessions to onboard users onto new tools, and establish best practices, playbooks, and documentation so solutions stick.

Requirements

• 5–8+ years software engineering background with production experience building and shipping systems.
• A proven track record of owning outcomes, not just outputs — someone who prioritizes ruthlessly, holds themselves accountable to results, and doesn't consider something shipped until it's working in the hands of users.
• Strong product instincts — comfortable looking at a messy list of requests and identifying the highest-leverage opportunity, defining what "done" means, and saying no to work that won't move the needle.
• Genuine obsession with customer experience — you think about how real people (advisors, internal teams) will interact with what you build, and you iterate based on their feedback rather than assumptions.
• Comfort reasoning about cost-to-serve, efficiency tradeoffs, and ROI — you make decisions about what to build and how based on business impact, not just technical interest.
• Strong proficiency in at least one modern language (Python preferred), comfort picking up new frameworks quickly, and fluency with AI coding assistants — using them to ship more, faster, without sacrificing reliability or code quality.
• Hands-on experience building with LLMs (OpenAI, Anthropic, Gemini, open-source), agent frameworks (LangChain, LlamaIndex, CrewAI, or similar), and a strong intuition for prompt engineering, RAG architectures, and the practical limits of AI in production — including how to evaluate tools and models on cost, latency, accuracy, and maintainability tradeoffs.
• Comfortable working with CRM platforms (we use Salesforce, including Service Cloud and Experience Cloud) or confident ramping up quickly.

Qualifications

• Self-directed and proactive — you identify opportunities, propose solutions, and drive them to completion without heavy oversight, even through initial ambiguity.

Skills

• Strong proficiency in at least one modern language (Python preferred), comfort picking up new frameworks quickly, and fluency with AI coding assistants — using them to ship more, faster, without sacrificing reliability or code quality.
• Hands-on experience building with LLMs (OpenAI, Anthropic, Gemini, open-source), agent frameworks (LangChain, LlamaIndex, CrewAI, or similar), and a strong intuition for prompt engineering, RAG architectures, and the practical limits of AI in production — including how to evaluate tools and models on cost, latency, accuracy, and maintainability tradeoffs.
• Comfortable working with CRM platforms (we use Salesforce, including Service Cloud and Experience Cloud) or confident ramping up quickly.

Benefits

• Competitive pay and equity for eligible positions.
• Premium healthcare, dental, and vision insurance plans (HMO and PPO).
• 401k savings plan with a 4% match and immediate vesting.
• 16 week paid parental leave after one year of employment.
• Professional growth and development opportunities including an employee mobility program and an annual L&D budget allocation for each employee.
• Company perks program (includes discounts on pet insurance, fitness, cell phone plans, and travel, etc.).
• Financial guidance program (includes counseling on navigating debt, tracking personal spend, saving and planning goals, home-purchasing preparedness, etc.).
• One month work from anywhere policy (with the exception of a few countries).

Pay

Base salaries will be reviewed at regular intervals throughout the year, typically in conjunction with performance review cycles. By evaluating compensation on a regular basis, we are able to reward high performance and ensure all employees have opportunities for growth.

Schedule

This is a hybrid role, requiring three days per week in our San Francisco, Culver City, or Dallas office.