Lead AI Engineer

Job Description

Job Description What is the Opportunity? Lead the development of enterprise-scale autonomous AI agents that transform RBC's Site Reliability Engineering operations. You'll architect and build intelligent agents using LangChain, LangGraph, and Claude that autonomously diagnose, resolve, and optimize production systems. This "lead-by-doing" role combines 70% hands-on engineering with 30% leadership, with full accountability from concept to production. Mentor 2-3 engineers, shape GAIA's agentic roadmap, and establish reusable frameworks that drive business impact across RBC. Every architectural decision is backed by working code. Work on cutting-edge agentic AI solutions that enable self-healing systems and drive innovation in autonomous operations at enterprise scale. What Will You Do? Code, architect, build, deploy, and maintain enterprise-scale agentic AI solutions with full accountability for scalable architecture and SLA maintenance Build and ship autonomous agents that diagnose, resolve, and optimize production systems including self-healing infrastructure and dynamic disaster recovery Design multi-agent stateful workflows using LangChain, LangGraph, Claude Agentic Skills, and Model Context Protocol (MCP) with human-in-the-loop patterns Contribute to GAIA's Agentic Use Case Roadmap, prioritizing initiatives by business impact, technical feasibility, and ROI Demonstrate reusable frameworks through working code and share knowledge via Knowledge Sessions and Engineering Council presentations Provide technical guidance through pair programming and code reviews, mentoring 2-3 engineers on hands-on engineering excellence Implement automated incident resolution, compliance monitoring, and security remediation capabilities for production operations Ensure every architectural decision is backed by working code with zero delegation-only work What Do You Need to Succeed? Must Have Bachelor's degree in Computer Science, Software Engineering, Data Science, or related quantitative field 5 years professional software engineering experience with 2-3 years focused on Gen AI, AI agents, and autonomous systems development Deep expertise with LangChain and LangGraph frameworks; proven experience with production-grade agentic systems (CrewAI, AutoGen) Python mastery (FastAPI, Pydantic, async programming), backend API design (RESTful, GraphQL), and React/TypeScript for HITL interfaces Proven track record delivering production-ready AI solutions with strong understanding of scalable architecture and distributed systems Knowledge of LLM orchestration, tool use/function calling, multi-agent workflows, prompt engineering, and RAG architectures Nice to Have Proficiency in Azure, AWS, or GCP within regulated/enterprise environments and experience with Infrastructure as Code (Terraform, Ansible) Understanding of SRE principles, frameworks, observability, incident management, and reliability engineering practices Knowledge of monitoring concepts (logs, metrics, traces, tel

Required Skills