Job Description
The AI/ML Engineer is responsible for integrating AI capabilities into enterprise platforms, products, and business workflows.
This role focuses on operationalizing AI solutions by integrating AI models and AI services into production systems, and enabling scalable, secure, and responsible AI adoption across the organization.
Key Tasks and Responsibilities:
- Apply broad knowledge of IT operations principles, business drivers, and related areas to impact results
- Build relationships with key functional stakeholders in the business and communicate appropriately with them
- Broad knowledge of various technologies (Windows 10, Windows 7, MS O365, Active Directory, Cisco UCS, Mobile Device Management, Cyber Security, Networking and Connectivity, Server Support, and Infrastructure Projects)
- Strong business acumen and the ability to translate technical terms into business terms required
- Responsible for day-to-day service operations. This includes providing regular infrastructure maintenance and support, with prompt resolution of issues, off-hours support, and compliance with IT governance and processes
- Proactively use root cause analysis to increase operational efficiency
- Effectively manage third-party service providers
- Liaise with vendors and application teams to drive the root cause analysis and problem resolutions
- Provide daily, weekly, and monthly reports to the appropriate audience
- Manage a team of IT support resources to provide best-in-class IT service to all functional users
- Manage performance of Level 2 & Level 3 services and support clients while ensuring service levels are achieved and customer expectations are met or exceeded
- Responsible for ensuring staff are meeting/exceeding expectations regarding performance and defined SLA metrics/benchmarks
- Work with senior leadership and management in the business units to communicate issues, resolutions, and impact on business, as well as report on Metrics/KPIs
- Develop end-user communications and ongoing technical training material is required
- Impact the quality of operations provided by internal and external operations teams
- Directly affects customer satisfaction through engagement with customers and by providing transparency into operational outcomes
- Manage and engage with external vendors & internal stakeholders to negotiate contracts and key deliverables of IT assets procurement and services
- Direct and oversee vendor work
- Integrate AI and ML capabilities into business applications, platforms, and processes using APIs, cloud AI services, and enterprise architecture patterns
- Translate business and functional requirements into AI-enabled solutions in collaboration with product, engineering, and data teams
- Deploy, monitor, and maintain AI solutions in production environments (CI/CD, MLOps, APIs, orchestration)
- Leverage pre-trained models, foundation models, and cloud AI services, adapting them to business needs rather than building models from scratch
- Ensure AI solutions meet standards for security, scalability, reliability, and responsible AI (privacy, ethics, compliance)
- Support application teams with AI integration guidance, best practices, and troubleshooting
- Continuously optimize AI-enabled systems based on performance, usage, and business impact
Essential Qualifications and Education:
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