Enterprise AI Lead

Responsibilities

• Design and build enterprise AI/LLM platforms, including model access layers, orchestration, prompt management, and evaluation capabilities
• Develop and deploy AI agents and orchestration frameworks to automate workflows and enable intelligent system behavior
• Arcitect and implement RAG pipelines and secure data integration patterns, connecting enterprise data to AI systems
• Build and operate MLOps pipelines supporting model deployment, monitoring, evaluation, and lifecycle management
• Build and operate production-grade AI-enabled applications and services, integrating AI into real operational workflows
• Define and implement AI strategy and governance with a focus on practical, enforceable standards
• Define and implement model assurance and risk management practices, including evaluation frameworks, guardrails, and observability
• Build and maintain operational data pipelines to support AI and analytics workloads
• Integrate AI capabilities into enterprise platforms, APIs, and business systems
• Lead rapid AI prototyping and experimentation, turning emerging capabilities into deployable solutions
• Build and evolve an AI enablement platform, including reusable services, implementation playbooks, guardrails, and a shared knowledge base, enabling teams to adopt AI capabilities consistently and efficiently
• Enable internal teams through reusable platform services, templates, and development patterns
• Contribute to enterprise BI and analytics capabilities, integrating AI-driven insights into decision-making workflows

Qualifications

• Strong experience building and operating platforms or infrastructure systems, with a shift into AI/ML or data platforms
• Hands-on experience developing and deploying AI/LLM-based systems in production
• Experience with LLMs, RAG architectures, embeddings, and agent-based systems
• Strong experience with data engineering and pipeline development
• Experience with MLOps practices, including model lifecycle management, deployment, and monitoring
• Proficiency in backend development (Python, Node.js, or similar) and API design
• Experience working in cloud environments (AWS, Azure, or GCP) with distributed systems
• Strong understanding of system design, scalability, and operational reliability
• Familiarity with secure or regulated environments and data protection requirements
• Ability to operate both hands-on as a builder and strategically as a technical leader