Cognitive Systems Engineer

Company Overview:

At Snap Finance, we believe everyone deserves access to the things they need, regardless of credit history. Since 2012, we've used data, machine learning, and a more human approach to create flexible financing solutions that help people move forward. We're proud of our inclusive, supportive culture, built on empowering our customers, partners, and team members alike. When our people thrive, so does our innovation.

If you're looking to make an impact and grow with a team that values you, come join us!

Job Description

How you'll make an impact:

• Design and build agentic analytics systems that can reason over data, generate insights, and take action with minimal human intervention 

• Define and manage the context lifecycle for agents (ingestion, memory, retrieval, pruning, and evaluation) 

• Write high-quality agent specifications (prompts, tools, workflows) that are modular, testable, and production-ready 

• Optimize token efficiency, latency, and cost across multi-agent workflows without sacrificing output quality 

• Develop automated orchestration frameworks for chaining agents, handling fallbacks, and managing state across complex tasks 

• Implement evaluation and quality control loops (automated scoring, human-in-the-loop, and self-healing systems) 

• Translate ambiguous business questions into structured, agent-executable analytics workflows 

• Build and maintain data pipelines and feature layers that support real-time and batch agent reasoning 

• Partner with analytics, engineering, and product teams to embed agentic systems into real business processes 

• Continuously experiment with new models, tooling, and architectures to push system capability forward 

What you'll need to succeed:

• Strong foundation in data analysis and/or data science (SQL, Python, statistical thinking, experimentation) 

• Experience building production-grade data systems or ML systems (pipelines, APIs, orchestration frameworks) 

• Working knowledge of LLMs and agentic architectures (prompt design, tool use, memory strategies, evaluation techniques) 

• Ability to think in systems, not just models—understanding how components interact, fail, and scale 

• Experience or strong interest in automation and autonomous workflows 

• Comfort with ambiguity and a bias toward building, testing, and iterating quickly 

• Clear, structured thinking with the ability to write precise specifications for both humans and machines 

• Strong engineering discipline around versioning, testing, observability, and performance optimization 

• Curiosity about the future of analytics and a drive to move beyond dashboards into decision systems 

Why Join Us:

• Generous paid time off

• Competitive medical, dental & vision coverage

• 401K with company match for US

• Company-paid life insurance

• Company-paid short-term and long-term disability