Senior Staff AI Infrastructure Engineer

The role

You will build the platform that powers AI-driven decisions by designing secure MCPs and API integrations. You will also contribute to model provider gateways, RAG pipelines, and vector database implementations.

What you will do

• Build the platform that powers AI-driven decisions.
• Design and ship secure MCPs and API integrations.
• Shape a strategy for how data is stored, persisted, and connected.
• Contribute to model provider gateways, RAG pipelines, and vector database implementations.
• Mentor peers and help set a higher technical standard for the team.
• Participate in an on call rotation.

Required qualifications

• 10+ years of senior-level engineering experience.
• Experience designing and scaling distributed systems.
• Hands-on experience building secure API integrations.
• Real AI fluency using AI-assisted coding tools like Claude Code or Cursor.
• Comfort with modern data platforms like Snowflake, vector databases (e.g., Pinecone, Weaviate, pgvector), and similar technologies.
• Familiarity with data lineage, access control, and data quality practices.
• Cloud engineering fundamentals (AWS).
• Infrastructure-as-code (Terraform or similar).
• Ability to write production-quality code in Python or a comparable language.

Nice to have

• Experience and proficient level of understanding using RAG pipelines, LLMs, and vector database implementations in production.
• Exposure to model provider gateways or local/open-source model routing.
• Personal AI projects such as running local models or building agent-to-agent workflows.
• Experience mentoring or upleveling junior and mid-level engineers.

Benefits

• Company Stock Plan
• Unlimited vacation
• Educational and wellness reimbursements
• $0 cost employee insurance plans

About the company

Ridgeline is the first front-to-back system of record for investment managers. The company was created to modernize an industry held back by outdated, disconnected technology.