Sr. Specialist - Platform Operations (AI & Agentic Systems)

Résumé du poste

Manage, scale, and optimize production-grade Kubernetes clusters while operationalizing AI and agentic systems. Lead implementation projects and drive operational excellence through automation, observability, and reliable infrastructure management.

Détails du poste

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 Platform Operations: Manage, scale, and optimize production-grade Kubernetes (k8s) clusters across multi-cloud or hybrid environments. GitOps & Deployment: Design and maintain automated application delivery pipelines using ArgoCD to ensure declarative environment states. Infrastructure as Code (IaC): Provision and manage cloud infrastructure using tools like Terraform, OpenTofu, or Pulumi. Observability: Implement and maintain robust monitoring, logging, and alerting systems using Prometheus, Grafana, and ELK/OpenSearch stacks. Reliability Engineering: Participate in on-call rotations, conduct blameless post-mortems, and minimize operational toil through automation. Developer Experience: Collaborate with software engineering teams to streamline onboarding and reduce friction in the software development lifecycle. AI and agentic workflows: Design, plan, and deploy changes to existing systems, driving operational excellence and introducing new solutions, including. 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. 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 Kubernetes Expertise: 2+ years of hands-on experience managing Kubernetes workloads, ingress controllers, storage, and networking. GitOps Practice: Proven experience implementing GitOps workflows, specifically configuring and troubleshooting ArgoCD at scale. CI/CD Pipelines: Strong familiarity with continuous integration tools like GitHub Actions, GitLab CI, or Jenkins. Automation & Scripting: Proficiency in programming languages like Go or Python, alongside strong Bash scripting skills. Linux Fundamentals: Deep understanding of Linux internals, container runtimes (Docker, containerd), and core networking concepts (DNS, TCP/IP). AWS: Hands-on experience with cloud infrastructure and services, with strong expertise in AWS architecture. AI concepts and tooling: Familiarity with (e.g., model integration, agentic frameworks, or AI-driven automation) and a strong interest in operationalizing AI systems. Nice to Have Experience building Internal Developer Platforms (IDPs) using tools like Backstage. Familiarity with service meshes such as Istio or Linkerd. Certification in Kubernetes Administration (CKA) or Security (CKS). 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. Come as You Are Nasdaq is an equal opportunity employer. We welcome applications from candidates of all backgrounds and identities. We are committed to fostering an inclusive workplace where diverse perspectives, experiences, and identities are valued and celebrated. We ensure that individuals with disabilities are provided with reasonable accommodation throughout the hiring process. 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.

Ce que vous ferez

Manage, scale, and optimize production-grade Kubernetes clusters while operationalizing AI and agentic systems. Lead implementation projects and drive operational excellence through automation, observability, and reliable infrastructure management.

Exigences

Requires 2+ years of hands-on experience with Kubernetes and GitOps workflows, specifically ArgoCD. Proficiency in Python or Go, Linux internals, and AWS cloud architecture is essential for this role.

Avantages

• Annual bonus • Equity • Comprehensive benefits • Growth opportunities

Compétences indiquées

• Kubernetes · Souhaitée
• CI/CD · Souhaitée
• Go · Souhaitée
• Docker · Souhaitée
• Amazon Web Services · Souhaitée
• Linux · Souhaitée
• Terraform · Souhaitée
• Python · Souhaitée

Autres compétences pertinentes

Relevées dans la description du poste. Confirmez les exigences importantes ci-dessus.

• Kubernetes
• GitOps
• ArgoCD
• Terraform
• Prometheus
• Grafana
• Python
• Go
• Bash
• Linux
• AWS
• Docker
• CI/CD
• AI frameworks
• Observability
• Infrastructure as Code
• Istio
• Agentic AI
• Self-Starter
• Argo CD
• Workplace Inclusivity
• Pipelines
• MLOps (Machine Learning Operations)
• Multi-Cloud
• Workflow Management
• Go (Programming Language)
• Pulumi
• Infrastructure as Code (IaC)
• Programming Languages
• Artificial Intelligence
• Amazon Web Services
• Automation
• Bash (Scripting Language)
• Cloud Infrastructure
• Continuous Improvement Process
• Continuous Integration
• CPT Coding
• Software Development Life Cycle
• DevOps
• Financial Services
• Github
• Global Marketing
• Incident Management
• Python (Programming Language)
• Operational Excellence
• Operations
• Reliability Engineering
• Prometheus (Software)
• Safety Monitoring
• Software Engineering

Domaines d’emploi

• Technology
• Software
• Data & Analytics
• Engineering
• Finance & Accounting
• Platform Operations Engineer
• Scheduler / Operations Coordinator
• Stock Clerks
• Production, Planning, and Expediting Clerks