Are you a technical leader who thrives at architecting agentic AI systems and shipping them in production? Do you want to help define how autonomous, tool-using AI agents get built into a real, customer-facing product? If so, we invite you to apply to join our AI Platform team, where we're building the future of investment management software. As a Principal Engineer on the AI Platform team, you will guide the architecture and development of Ridgeline's agentic AI platform while also directly contributing to product delivery. You'll help drive the design of the agentic systems, workflows, and capabilities that power our product, including how those agents access external data and use models efficiently, all in close partnership with the engineers who built the platform's foundation. This role offers broad, cross-company impact, working across teams throughout the firm to shape how AI capabilities are built and adopted, in a collaborative, high-agency team culture. What will you do? - Define and drive technical strategy and architecture for Ridgeline's AI platform and shared AI capabilities across the company. - Lead technical decisions that enable engineering teams across the firm to use AI platform capabilities in scalable, reliable, secure, and responsible ways. - Identify and resolve systemic technical obstacles that limit the availability, usability, extensibility, or reliability of the AI platform, including proactively engaging teams building one-off AI solutions to bring them onto the shared platform. - Establish engineering standards and architectural approaches that help teams make sound decisions as AI technologies and capabilities evolve, including reliability and evaluation standards for AI models in production. - Partner across Engineering, Product, Data, and other functions to connect AI platform investments to company priorities and customer outcomes, adapting your working style to collaborate with diverse engineering squads. - Architect solutions for integrating external data via retrieval-augmented generation, including connections to third-party data stores, and build systems for token-efficient AI usage such as model routing and code execution.
- Propose and evaluate new AI features to advance the platform's capabilities, and resolve technical debates to align teams around the right approach. Desired Skills and Experience - 15+ years of software engineering experience, with deep expertise in systems architecture. - Significant experience building and shipping an AI-powered product in production, including agentic loop design, structured responses, tool calling, Model Context Protocol (MCP), and retrieval-augmented generation (RAG). - Proven ability to design scalable, efficient system architectures and evaluate the right technologies for AI system components. - Experience establishing software development best practices and reliability/evaluation standards for AI models in production. - Full-stack experience across front-end and back-end AI product development; proficiency in Kotlin, TypeScript, and React. - Experience working with both Anthropic and/or OpenAI models and APIs. - Track record of driving technical or architectural decisions and aligning stakeholders across teams, especially amid competing viewpoints. - Demonstrated success integrating third-party data sources and delivering measurable improvements in AI model performance and token efficiency in production. Bonus - Experience with multi-agent systems, AI agent orchestration, or advanced model evaluation techniques. - Background in financial services or investment management. - Contributions to open-source AI/ML projects or publications in the space. About Ridgeline Ridgeline is the first front-to-back system of record for investment managers.
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