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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates extensive expertise in systems architecture and AI platform development, with a strong focus on building scalable, reliable, and efficient AI systems. Proven ability to establish engineering standards and integrate third-party data sources to enhance AI model performance.
Highest-signal resume keywords
Systems Architecture ExpertiseAI Product DevelopmentKotlin ProficiencyTypeScript ProficiencyReact Proficiency
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
AI Model Evaluation StandardsAgentic Loop DesignRetrieval-Augmented GenerationFull-Stack DevelopmentSoftware Development Best Practices
Soft Skills
Stakeholder AlignmentTechnical Decision-Making
Tools & Technologies
OpenAI APIsAnthropic Models
Industry Keywords
Financial ServicesInvestment ManagementOpen-Source AI/ML Contributions
Tech Stack
Tools & technologiesKotlinReactTypeScript
About the role
Key responsibilities & impact- Define and drive technical strategy and architecture for Ridgeline's AI platform and shared AI capabilities across the company
- Lead technical decisions enabling engineering teams to use AI platform capabilities in scalable, reliable, secure, and responsible ways
- Identify and resolve systemic technical obstacles affecting the availability, usability, extensibility, or reliability of the AI platform
- Engage teams building one-off AI solutions to bring them onto the shared platform
- Establish engineering standards and architectural approaches as AI technologies evolve
- Establish 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
- Architect external-data integrations via retrieval-augmented generation, including third-party data stores
- Build token-efficient AI systems such as model routing and code execution
- Propose and evaluate new AI features and resolve technical debates to align teams
Requirements
What you’ll need- 15+ years of software engineering experience, with deep expertise in systems architecture
- Significant experience building and shipping an AI-powered product in production
- Experience with agentic loop design, structured responses, tool calling, Model Context Protocol (MCP), and retrieval-augmented generation (RAG)
- Ability to design scalable, efficient system architectures and evaluate 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 with Anthropic and/or OpenAI models and APIs
- Track record of driving technical or architectural decisions and aligning stakeholders across teams
- Experience 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
- Bonus: background in financial services or investment management
- Bonus: contributions to open-source AI/ML projects or publications in the space
Benefits
Comp & perks- Company Stock Plan, subject to the applicable Stock Option Agreement
- Unlimited vacation
- Educational reimbursements
- Wellness reimbursements
- $0 cost employee insurance plans
- Career advancement opportunities