Principal Applied AI Engineer

Quick Facts

• Role: Principal Applied AI Engineer (remote-first, hybrid optional)
• Reports to: Director, AI Development

Description

Lead and hands-on build production-grade, Cephai-powered applied AI capabilities inside the CINC platform. You will guide a small engineering team to design and deploy reliable intelligent automation workflows, retrieval-based systems, and AI-driven operational tooling, integrating cleanly with the rest of the platform. This is a practical leadership role combining system design and applied AI engineering with mentorship and architectural pattern development.

Responsibilities

• Lead the direction of a product team in partnership with a Product Lead (two-in-the-box)
• Design and build production-grade, Cephai-powered systems that bring the right context into the work
• Collaborate with operations, product, design, sales, marketing, and client support to solve real client problems
• Support team members and raise the bar for quality and maintainability
• Help shape architectural patterns and engineering practices across the organization

Requirements

• 15+ years of software engineering experience with fluency in Python, Node, TypeScript
• Experience designing and deploying production AI architectures (backend engineering plus agent orchestration)
• Working knowledge of LangGraph, LangChain, or similar orchestration frameworks
• Practical experience building AI-enabled applications using OpenAI, Anthropic, and Bedrock APIs (context management, streaming, evaluation)
• Familiarity with vector databases, semantic search, and embedding pipelines
• Strong software engineering fundamentals: API design, microservices, and integration patterns (service mesh, API gateway, event-driven)
• Practical experience with cloud-native environments (AWS or Google Cloud or equivalent), including serverless and containerized deployments
• Demonstrated ability to lead through influence and raise standards for quality
• Ability to explain complex trade-offs and design decisions to both technical and non-technical audiences
• Experience mentoring engineers and contributing to architectural strategy

Benefits

• AI-powered features ship faster with greater reliability and lower operational complexity
• Internal teams adopt shared AI patterns and tooling you help define
• Product and engineering teams see you as a trusted partner and technical leader
• The AI stack evolves with clarity, safety, and measurable impact for users
• “Less Tedious. More Meaningful.” for people using the platform every day