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

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.

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.

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.

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