Chief Python Software Engineer

We are seeking a Chief Python Software Engineer to join a small team of senior developers building a next-generation AI-powered financial assistant platform, rapidly iterating with business users to test, refine, and deploy chat, reporting, and bespoke interfaces into investment workflows. Responsibilities Collaborate with a small team of highly competent, hands-on engineers in a startup-style environment with minimal formality Work directly with sophisticated, technical stakeholders without the need to interface with non-technical clients or users Gather low-level requirements from high-level task definitions and consider edge cases before implementation Produce system designs and deliver production-grade implementations with high autonomy and self-governance Shape and influence product direction and architecture decisions Build and maintain systems using cutting-edge technology without legacy constraints Adopt new languages and technologies as the team evolves its stack Optimize AI applications across quality, latency, reliability, and cost Review, test, and validate AI-generated code produced through coding agents Monitor AI behavior in production and conduct failure analysis and regression testing Maintain a high bar for quality, reliability, security, and maintainability across deliverables Requirements 7+ years of experience in Python, React (TS), or other programming languages Desire and readiness to learn Python if not already proficient Experience with FastAPI or other Python frameworks, along with AWS, Kubernetes, and Terraform High autonomy and self-governance in handling loosely defined tasks, from requirements gathering to design and delivery Readiness to work in a startup environment and continuously learn new languages and technologies High bar for quality and reliability in software delivery Experience with FE work, including TS/JS, React/NextJS/Node Proficiency in AI-assisted programming methods and tools, including coding agents for code generation Experience with AI evaluation and quality engineering, including automated evaluations, test datasets, regression testing, and failure analysis Understanding of AI security and production controls, including data privacy, access control, prompt-injection risks, guardrails, and auditability Ability to optimize AI applications across quality, latency, reliability, and cost Ability to learn and adopt new technologies rapidly as the AI ecosystem evolves Advanced proficiency in English (C1+)