Senior AI Engineer

Key Responsibilities

• Design, build, deploy, and maintain enterprise AI and machine learning solutions.
• Develop and operationalize generative AI applications leveraging large language models (LLMs), retrieval-augmented generation (RAG), copilots, and intelligent automation.
• Partner with business leaders to identify high-value AI use cases aligned to strategic priorities.
• Build scalable AI pipelines, APIs, and integrations with enterprise platforms and business applications.
• Collaborate with data engineering teams to ensure high-quality, governed, and accessible data for AI initiatives.
• Develop AI-enabled analytics and predictive models supporting manufacturing, supply chain, customer service, sales, and operations.
• Implement AI governance, model monitoring, security, and responsible AI practices.
• Optimize model performance, scalability, reliability, and operational efficiency.
• Evaluate emerging AI technologies and recommend enterprise adoption strategies.
• Support AI experimentation, rapid prototyping, and innovation initiatives across the organization.
• Create technical documentation, operational procedures, and knowledge transfer materials.
• Mentor technical teams and promote AI engineering best practices.

Requirements

• Required: Bachelor’s degree in Computer Science, Information Technology, Data Science, Engineering, or a related field. Advanced degree in Artificial Intelligence, Machine Learning, or Data Science preferred.
• Required: 8–10+ years overall technology experience, 5+ years focused in AI/ML engineering.
• Required: Proven experience deploying enterprise-scale AI systems.
• Required: Strong experience with AI architecture and distributed systems.
• Required: Proven experience operationalizing generative AI at scale.
• PREFERRED: Experience with Microsoft Copilot, Azure OpenAI, or enterprise generative AI platforms.
• PREFERRED: Manufacturing, supply chain, consumer products, or retail industry experience.
• PREFERRED: Experience with MLOps, vector databases, orchestration frameworks, and AI observability platforms.
• PREFERRED: Familiarity with data visualization and analytics platforms such as Power BI or Tableau.
• PREFERRED: Experience leading enterprise AI transformation initiatives.
• PREFERRED: AI governance frameworks, FinOps for AI workloads, multi-cloud AI strategy.