Kueski

Full-stack Engineer

• Evolve Kueski's existing services, data platforms, and pipelines into systems that AI agents and models can operate on safely and effectively
• Decide what infrastructure to wrap, refactor, expose, or retire, and sequence the transformation
• Structure and make Kueski's code, data, business logic, documentation, and operational state retrievable for LLMs and agents
• Own the retrieval, memory, and knowledge-representation layer
• Redefine software development around agentic engineering workflows covering specifications, coding, review, testing, and deployment
• Set standards, tooling, and guardrails that integrate AI into the development lifecycle
• Design and ship agentic systems for internal workflows
• Take at least one high-stakes AI capability through production and demonstrate its impact with data
• Establish evaluation harnesses, observability, and safety/compliance guardrails for AI in a regulated lending environment
• Address PII handling, model risk, and auditability
• Build reusable platforms and reference implementations
• Increase engineering-wide AI-native fluency through collaboration and mentorship
• Turn one-off successes into self-sustaining capabilities

Staff AI Software Engineer