Lead AI Engineer

Essential Duties And Responsibilities

• Architect, design, develop, deploy, and support enterprise-scale Agentic AI solutions.
• Build and maintain scalable AI systems utilizing Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) pipelines, model orchestration frameworks, agentic architectures, and secure APIs.
• Design and implement AI-powered automation solutions that improve business processes, operational efficiency, and decision-making capabilities.
• Collaborate with cross-functional teams, including data scientists, software engineers, infrastructure teams, product managers, and business stakeholders, to translate business requirements into AI-driven solutions.
• Ensure AI applications adhere to enterprise security standards, governance frameworks, privacy requirements, and regulatory compliance obligations.
• Lead the integration of AI solutions with enterprise systems, applications, and cloud-based platforms.
• Evaluate emerging AI technologies, tools, and platforms to identify opportunities for innovation and business value creation.
• Contribute to the development and execution of the enterprise AI strategy and digital transformation roadmap.
• Build and enhance core AI capabilities that support long-term enterprise objectives.
• Maintain awareness of industry trends, advancements, and best practices in artificial intelligence, machine learning, and cloud technologies.

Qualifications

• Education: Bachelor's degree in Computer Science, Engineering, Data Science, Artificial Intelligence, or a related technical field required. Master's degree in a relevant discipline preferred.
• Experience: Extensive experience designing, developing, and deploying enterprise AI and machine learning solutions. Experience working with Large Language Models (LLMs), Agentic AI frameworks, and Retrieval-Augmented Generation (RAG) architectures. Demonstrated experience leading complex technical initiatives and cross-functional projects. Experience developing cloud-native applications and distributed systems in enterprise environments. Proven ability to mentor and guide engineers within a technical organization.
• Knowledge, Skills, and Abilities: Advanced knowledge of artificial intelligence, machine learning engineering, and generative AI technologies. Strong understanding of Agentic AI frameworks, model orchestration platforms, LLMs, and RAG architectures. Expertise in cloud infrastructure, distributed computing, and scalable system design. Knowledge of AI security, governance, compliance, and risk management practices. Proficiency in API design, integration patterns, and enterprise application architecture. Strong analytical, problem-solving, and decision-making skills. Excellent collaboration and communication skills with the ability to engage technical and non-technical stakeholders. Ability to evaluate emerging technologies and recommend strategic solutions aligned with business objectives. Demonstrated leadership, coaching, and mentoring capabilities.

Compensation

Compensation is based on a range of factors that include relevant experience, knowledge, skills, other job-related qualifications.