Staff Engineer or Architect (AI Agentic Team)

Join our AI Agentic Team as a Staff Engineer or Architect. In this role, you will design, build, and own agent systems from start to finish, leveraging AI and emerging technologies to improve productivity and decision-making. You will work in a compliance-heavy, globally regulated domain and set a technical vision for your team. The ideal candidate has 8+ years of software engineering experience, hands-on experience with LLMs, and a background in financial services or compliance-heavy environments.

If you don’t see yourself fully reflected in every job requirement listed on the posting above, we still encourage you to reach out and apply

Responsibilities

• Design, build, and own agent systems end-to-end for identity, fraud, risk, and commerce workflows, ensuring reliability and observability.
• Build reliable, steerable, multi-step agent workflows that plan, execute, observe outcomes, and iteratively improve, including tool use and human-in-the-loop patterns.
• Leverage AI and emerging technologies to improve productivity, streamline workflows, and identify opportunities for continuous improvement while ensuring compliance.
• Demonstrated ability to own features end-to-end and communicate trade-offs clearly to both technical and non-technical stakeholders
• Multi-agent orchestration patterns and production-grade evaluation harnesses

Requirements

• Fluency using AI agents in your own engineering workflow - you can show us how you keep a mental model, verify outputs, and stay accountable while moving faster with AI
• 8+ years of software engineering experience with demonstrated impact on production systems
• Experience working on challenging, novel, or ambiguous projects where you had to define the problem, not just solve a handed-down spec
• Hands-on experience building with LLMs - prompt engineering, RAG, tool use, and at least one agent framework (e.g. LangGraph, CrewAI, AutoGen, or similar), plus evaluation frameworks for agent behavior
• Vector databases, knowledge graphs, or structured retrieval for agent memory

Preferred

• AI observability tooling; MLOps practices (experiment tracking, model registries, feature stores)
• Experience in financial services, identity, fraud, or risk domains, or other compliance-heavy environments (AML, fraud rules engines, identity graphs, risk scoring)