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AI Technical Lead – GenAI & Agentic AI
Location
United States
Posted
4 days ago
Salary
0
Seniority
Lead
No structured requirement data.
Job Description
AI Technical Lead – GenAI & Agentic AI
Moder
Role Description The AI Technical Lead is responsible for leading the design, architecture, development, and deployment of enterprise-scale Generative AI and Agentic AI solutions that drive business transformation and innovation. This role combines deep technical expertise in Large Language Models (LLMs), Agentic AI systems, cloud-native AI platforms, and AI engineering best practices with strong customer engagement and technical leadership capabilities. - Lead the end-to-end design and delivery of Generative AI and Agentic AI solutions. - Define reference architectures, implementation patterns, and engineering standards for enterprise AI applications. - Evaluate emerging AI technologies and frameworks and recommend adoption strategies. - Ensure AI solutions align with enterprise architecture, security, governance, and scalability requirements. - Architect and implement Agentic AI systems, including: - Multi-agent workflows - Agent orchestration patterns - Memory architectures - Tool integration frameworks - Retrieval-Augmented Generation (RAG) solutions - Design AI agents capable of interacting with enterprise systems, APIs, business processes, and knowledge repositories. - Establish reusable frameworks for autonomous and semi-autonomous agent execution. - Lead development of AI-powered applications utilizing LLMs, foundation models, and enterprise knowledge sources. - Guide engineering teams in implementing production-grade AI architectures and services. - Define and implement AI evaluation frameworks covering: - Response quality - Groundedness - Hallucination detection - Agent performance - Safety and reliability - Establish AI monitoring, observability, and operational performance standards. - Support responsible AI, governance, compliance, and model risk management practices. - Develop metrics and measurement frameworks to assess business and technical outcomes. - Design, deploy, and optimize AI solutions across Azure, AWS, and Google Cloud environments. - Collaborate with platform teams to establish scalable and secure AI infrastructure. - Drive adoption of cloud-native architectures, LLMOps, MLOps, and automation practices. - Champion adoption of AI-assisted development platforms including: - Claude Code - GitHub Copilot - Cursor - Equivalent AI engineering tools - Work directly with customers to understand business challenges and identify AI-driven opportunities. - Translate business requirements into scalable technical architectures and implementation plans. - Lead technical workshops, architecture reviews, proofs of concept, and solution demonstrations. - Serve as a trusted advisor on AI strategy, implementation, and operationalization. Qualifications - Advanced Python development - Large Language Models (LLMs) - Generative AI application development - Retrieval-Augmented Generation (RAG) - Agentic AI architectures - Multi-agent systems - Model Context Protocol (MCP) - Tool-calling and agent orchestration frameworks - AI evaluation and observability platforms - Cloud platforms (Azure, AWS, Google Cloud) - API design and integration - Enterprise application architecture Requirements - Experience with LangGraph, CrewAI, AutoGen, Semantic Kernel, or similar agent orchestration frameworks. - Experience implementing AI governance, responsible AI, and model risk management frameworks. - Familiarity with MLOps, LLMOps, CI/CD pipelines, and cloud-native deployment models. - Experience leading enterprise-scale AI transformation initiatives. - Banking & Financial Services industry experience, including exposure to customer servicing, operations, risk, underwriting, fraud, claims, or compliance use cases. Education and/or Experience - Bachelor's degree in Computer Science, Engineering, Information Technology, Data Science, or a related field. - 10+ years of experience in Artificial Intelligence, Machine Learning, Data Science, Software Engineering, or related technical disciplines. - Demonstrated experience leading complex AI solution delivery programs from concept through production deployment. - Proven experience working directly with business stakeholders and customers in consulting or solution delivery environments.
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