AI Engineering Leader

AI Engineering Leader Locations: Austin, TX | Charlotte, NC | New York, NY | Tempe, AZ | San Diego, CA, (hands on AI) Role Overview We are seeking a highly hands-on AI Engineering leader with deep expertise in Generative AI, Agentic systems, and production-grade AI platforms. This role is not a pure management role — the ideal candidate will actively design, build, and scale AI systems (RAG, agents, evaluation frameworks) while leading engineering initiatives and influencing platform strategy. The candidate must demonstrate strong AI + AWS cloud expertise, with proven experience delivering enterprise-grade AI solutions in production environments. Core Responsibilities AI System Design & Development • Design and build production-grade GenAI systems, including: • Multi-agent architectures • Retrieval-Augmented Generation (RAG) pipelines • GraphRAG implementations • Autonomous agent workflows and orchestration • Develop and integrate AI agents with tools, APIs, and enterprise systems • Implement MCP-based agent communication and tool-use frameworks • Apply advanced prompt engineering techniques for reliability and performance Agentic AI & Evaluation • Build and deploy multi-agent orchestration systems • Develop and implement: • Agent evaluation frameworks • RAG evaluation pipelines • Measure and optimize: • Output quality • Hallucination rates • Relevance and groundedness • Continuously improve models through evaluation-driven iteration Engineering & Platform Development • Develop APIs and services using: • Python (primary) • .NET (preferred) • Build scalable AI services with: • REST APIs • Microservices architecture • Contribute to web-based AI applications using: • Angular / TypeScript (preferred) • Integrate AI systems into enterprise workflows and applications Cloud & Infrastructure (AWS Focus) • Design and deploy AI solutions on AWS, leveraging: • Lambda, S3, EC2, EKS, Glue, SNS, SQS • Kafka-based streaming architectures • Build scalable and secure AI pipelines using cloud-native patterns • Implement cost-efficient and high-performance AI workloads DevOps & CI/CD • Design and implement CI/CD pipelines using GitHub Actions • Integrate AI workflows into CI/CD pipelines with strong AWS integration • Ensure: • Automated deployment • Testing and validation of AI systems • Continuous monitoring and iteration AI Development Tooling • Leverage modern AI development tools and ecosystems, including: • Claude (Claude API / Claude Code) • Cursor AI (AI-assisted development workflows) • Build and optimize developer workflows using AI-assisted coding tools Required Qualifications • 10+ years of overall engineering experience • 5+ years of hands-on AI/ML / GenAI development in production environments • Strong experience building: • AI agents (minimum 2+ implementations) • GraphRAG systems (minimum 2+ implementations) • MCP-based integrations (minimum 1+) • Proven expertise in: • Multi-agent orchestration • RAG pipelines • Agent and RAG evaluation frameworks • Strong programming skills in: • Python (must-have) • Experience with: • API development and system integration • Strong experience with: • AWS cloud platform (must-have) Preferred Qualifications • Experience with: • .NET / C# development • Terraform (Infrastructure as Code) • Experience building: • Web applications using Angular / TypeScript • Familiarity with: • Kafka-based streaming systems • Exposure to: • Advanced AI orchestration frameworks (LangChain, LangGraph, etc.)