Sr AI Customer Engineer (LLM, RAG, LangGraph)

The Opportunity

The AI Customer Engineer is our entry point into technical customer success — a hands-on executor who learns by doing, builds foundational platform knowledge, and contributes to reliable, well-documented customer solutions. This role works in structured environments under clear guidance, following patterns set by more senior roles. Success here is about learning deeply, executing reliably, and building the habits of quality and repeatability that define great Customer Engineers at every level.

What You'll Contribute

• Analyze recurring and complex customer-impacting engineering issues and identify opportunities for AI-driven automation.
• Build AI-powered tools and workflows that help engineers diagnose, troubleshoot, remediate, and prevent customer issues.
• Develop prompt harnesses and evaluation frameworks to systematically test LLM solutions against real-world engineering scenarios.
• Coding, logs, configurations, documentation, tickets, incidents, and other engineering context to build grounded AI solutions.
• Design agentic workflows where LLMs can reason over context, use tools, perform actions, validate results, and iterate.
• Understand and optimize the complete LLM loop:
• Context → Prompt → Model → Tool → Observation → Validation → Iteration
• Investigate AI failures methodically and improve prompts, context, tools, model selection, and workflows.
• Build prototypes quickly and turn successful experiments into reliable, reusable engineering capabilities.
• Develop automation that can identify patterns across customer issues and surface potential root causes or recommended actions.
• Measure solutions using meaningful engineering metrics such as accuracy, resolution time, automation rate, reliability, latency, and cost.
• Partner with internal engineering teams to integrate AI capabilities into existing tools and workflows.
• Help establish reusable patterns for applying AI to customer engineering problems at scale.

What We're Seeking

• Early-career experience in a technical implementation or customer-facing role, with a demonstrated ability to translate well-defined requirements into concrete technical tasks across configuration, integration, and deployment scenarios.
• Experience in LLM Application Development: Hands-on experience building production applications using LLMs, prompt engineering, structured outputs, and function/tool calling.
• Experience in AI Agents & Orchestration: Experience building agentic workflows using frameworks such as LangGraph, LangChain, or equivalent, including MCP/tool integrations.
• Experience in Production AI Engineering: Strong Python/software engineering skills with experience deploying, monitoring, evaluating, and optimizing AI workloads for reliability, latency, cost, and security.
• Basic working knowledge of enterprise software platforms, APIs, and integrations, with a willingness to develop fluency in FICO Platform, decision management, and related analytics and fraud capabilities.
• Ability to document solutions, runbooks, and support procedures to ensure long-term maintainability, and to flag early-stage risks such as data gaps and environment constraints to senior team members.
• Comfortable working within structured team environments under guidance, with clear communication of technical progress and issues to both customer and internal teams.
• A proactive approach to continuous skill development with demonstrated curiosity, reliability, and professionalism in customer-facing situations — even under ambiguity.

Our Offer to You

• An inclusive culture strongly reflecting our core values: Act Like an Owner, Delight Our Customers and Earn the Respect of Others.
• The opportunity to make an impact and develop professionally by leveraging your unique strengths and participating in valuable learning experiences.
• Highly competitive compensation, benefits and rewards programs that encourage you to bring your best every day and be recognized for doing so.
• An engaging, people-first work environment offering work/life balance, employee resource groups, and social events to promote interaction and camaraderie.