The Role

As a Sr. Specialist - Platform Operations you'll play a critical role in keeping Nasdaq's platforms - including our emerging AI and agentic AI systems - running reliably and efficiently. You'll support global markets and clients through strong technical operations, incident management, and continuous improvement, while helping operationalize the next generation of intelligent, automated services.

You'll thrive in this role if you're a self-starter who enjoys solving complex operational challenges, works well across teams, and brings a passion for technology, AI, and automation to a fast-paced, high-impact environment.

Key Responsibilities

• Manage day-to-day technical operations and application support, including AI-powered and agentic AI applications, while ensuring service continuity for internal and external customers.

• Design, plan, and deploy changes to existing systems, driving operational excellence and introducing new solutions, including AI and agentic workflows.

• Lead and contribute to implementation projects, from requirements through to launch and ongoing improvement, with a focus on deploying, scaling, and monitoring AI and agentic services.

• Monitor, troubleshoot, and resolve incidents across traditional and AI-driven systems, while maintaining clear and accurate operational documentation and procedures.

• Identify and implement automation and process improvements, leveraging AI and agentic tooling to enhance how systems are tested, deployed, and maintained.

• Support the operational reliability, observability, and responsible/governed use of AI models and agents, including performance, cost, and safety monitoring.

Required Qualifications

• Bachelor's degree in Computer Science, Information Systems, or a related field.

• 2-3 years of experience in technical operations, system administration, application support, or related areas.

• Hands-on experience with cloud infrastructure and services, with strong expertise in AWS architecture.

• Proficiency in Linux/Unix environments and Kubernetes (k8s).

• Experience with infrastructure-as-code, scripting, and automation tools, as well as CI/CD pipeline design, version control, and GitOps practices.

• Familiarity with AI concepts and tooling (e.g., model integration, agentic frameworks, or AI-driven automation) and a strong interest in operationalizing AI systems.

Nice to Have

• AWS certification(s).

• Experience with Kubernetes-based environments in cloud or hybrid settings.

• Experience with ArgoCD.

• Background in DevOps practices within a regulated or financial services environment.

• Experience deploying or operating AI/agentic applications (e.g., model serving, MLOps, monitoring, or agent orchestration frameworks).

• Familiarity with AI observability, evaluation, and cost/performance optimization for production AI workloads.

This position will be located in Toronto or Philadelphia, and offers the opportunity for a hybrid work environment at least 3 days a week in-office, subject to change, providing flexibility and accessibility for qualified candidates.

Applicants must be authorized to work in the U.S. or Canada, without the need for employment-based visa sponsorship now or in the future; Nasdaq will not sponsor applicants for U.S. work visa status for this opportunity (no sponsorship is available for H-1B, L-1, TN, O-1, E-3, H-1B1, F-1, J-1, OPT, CPT or any other employment-based visa)

This posting is for an existing vacancy within Nasdaq.

What We Offer

We're proud to offer a competitive rewards package that is meaningful, recognizes the unique needs of our employees and their families and incentivizes employees for their contribution to Nasdaq's overall success.

The base pay range for this role is $91,000 - $129,000. In addition to base salary, Nasdaq provides a generous annual bonus/commission (short-term incentive), and equity (long-term incentive), comprehensive benefits, and opportunity for growth. Exact compensation may vary based on several job-related factors that are unique to each candidate, including but not limited to: skill set, experience, education/training, business needs and market demands.