Description

• Build AI-native product features that combine strong software engineering with applied data science and machine learning techniques.
• Create and refine automated AI agent systems written primarily in Python.
• Design agentic workflows that can reason over business and financial data, use tools safely, retrieve relevant context, and produce useful outputs within clear guardrails.
• Develop backend services, APIs, data pipelines, and integrations that connect our AI products to internal and external data sources.
• Build evaluation, observability, and feedback loops for LLM-powered systems, with attention to accuracy, reliability, latency, cost, and user experience.
• Partner with product, design, and business stakeholders to translate ambiguous customer needs into practical technical systems.
• Support existing products and features, while helping design and build new ones.
• Collaborate regularly with other stakeholders and partners to solicit requirements, seek feedback, and provide updates.

Qualifications

Candidates do not need prior experience with every technology in our stack - we are looking for candidates who are excited to learn new frameworks. That said, strong Python experience, applied data science and machine learning experience, and experience building agents are needed.

• Strong professional experience building production software systems.
• Strong Python experience, including writing robust, testable, maintainable production code.
• Applied data science and machine learning experience, including comfort working with structured data, model outputs, evaluation methods, and probabilistic systems.
• Experience building AI agents, agentic workflows, LLM-powered automation, or similar systems that interact with tools, APIs, documents, or databases.
• Strong relational database fundamentals, including SQL and practical data modeling.
• Demonstrable proficiency and a track record of professional success coding in at least two programming languages.
• Excellent written and verbal communication skills.
• Enjoy working in a collaborative environment where engineers are expected not only to build great technology, but also to define project vision, specify technical strategy, and always be learning.
• Experience presenting to audiences and communicating effectively and empathetically with clients and other stakeholders.

Strong preference will be given to candidates who have experience:

• Building AI products that reached real users, especially in accuracy-sensitive or data-rich domains.
• Designing LLM evaluation workflows, test sets, prompt iteration processes, model selection approaches, and production monitoring for AI systems.
• Working with retrieval-augmented generation, embeddings, vector search, structured extraction, classification, ranking, or other applied ML techniques.
• Quickly learning new languages, frameworks, and technologies, including best practices.
• With relational databases and query optimization.
• Deploying on and configuring Google Cloud.
• Writing production-ready code in Elixir, TypeScript, JavaScript, Go, or Ruby.
• Working across the full product surface, including frontend technologies like TypeScript, React, GraphQL, and Relay

Key Skills

Education

Bachelor's degree