Jobs · Engineering

Sr Staff AI Platform Engineer

Ladders · United States · 1 wk ago
RemoteRemoteEngineering$220k–$256k/yrFull-time

About the role

For our client, we are seeking a Sr Staff AI Platform Engineer to join the team of a leader in the Finance & Insurance space. This role will shape the technical foundation for AI-enabled platforms that support secure, scalable, and high-performance enterprise use cases. The ideal candidate will lead roadmap definition, architectural strategy, and engineering standards across multiple teams while helping advance next-generation AI capabilities. This position also partners closely with engineering stakeholders to prototype emerging patterns, improve developer workflows, and strengthen platform reliability and throughput.

Responsibilities

  • Define and own the 3–5 year technical roadmap for a high-scale, AI-ready data lakehouse
  • Prototype and benchmark emerging AI architectural patterns and technologies
  • Set standards for code quality, CI/CD processes, and system design
  • Design platform-level interfaces for agentic workflows with robust human-in-the-loop mechanisms
  • Build secure access and interpretation layers for enterprise data

Qualifications

  • 15+ years of software engineering experience
  • Expertise in Java or Scala, and Python
  • Experience building extensible frameworks, high-throughput APIs, and developer libraries
  • Hands-on experience with multi-agent orchestration and transitioning to agentic RAG
  • Knowledge of the Model Context Protocol (MCP) for AI agent interoperability
  • Experience implementing AI-native CI/CD features and automated workflows for human approval

Benefits

  • Opportunity to work at the cutting edge of AI technology and platform engineering
  • Access to a high-performance software environment focused on reducing latency and increasing throughput
  • Engagement with emerging trends in the AI ecosystem, including multi-agent technology and reasoning-based retrieval
  • Flexibility to influence architectural choices across multiple teams and projects

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