American Express
American Express
American Express एक वैश्विक वित्तीय सेवा कंपनी है, जो बैंकिंग, वित्त और B2B भुगतान के क्षेत्र में काम करती है। इसके व्यवसाय में उपभोक्ता, व्यवसाय और कॉर्पोरेट क्रेडिट कार्ड; भुगतान और मर्चेंट सेवाएँ; बचत खाते, सावधि जमा और व्यक्तिगत ऋण; साथ ही रिवॉर्ड, यात्रा कार्यक्रम, कॉर्पोरेट भुगतान समाधान, वित्तीय शिक्षा, सुरक्षा सेवाएँ तथा कार्डधारक और मर्चेंट सहायता शामिल हैं।

Infrastructure Engineer II, Core Platforms

Build scalable GPU-enabled infrastructure for American Express’s enterprise AI workloads. Bring Kubernetes, AIOps, observability, and infrastructure-as-code together to support production platforms.

विवरण

  • Create infrastructure deployments that meet technical requirements and standards.
  • Maintain clear technical design and implementation documentation.
  • Keep platform infrastructure available and performant by finding and resolving issues.
  • Assess existing systems, gather requirements, and identify improvements to infrastructure design and deployment.
  • Connect infrastructure components to improve resilience, scalability, efficiency, and strategic fit.
  • Plan and run tests to confirm solutions meet business and technical requirements.
  • Address technical issues across the project lifecycle and escalate critical problems as needed.
  • Work with project teams to ready infrastructure components for production.
  • Use AI-assisted tools and prompt engineering in deployment, monitoring, and infrastructure support workflows.
  • Review AI-generated recommendations and detect infrastructure anomalies, capacity constraints, deployment risks, and operational issues.
  • Help produce runbooks, troubleshoot incidents, summarize postmortems, analyze logs, and support human-reviewed operations.
  • Integrate machine-learning AIOps tools to detect anomalies, predict failures, and correlate incidents across distributed systems.
  • Use GitHub Copilot, Claude Code, Cursor, and similar tools to develop and check Terraform, Ansible, and Kubernetes infrastructure-as-code.
  • Build and run GPU- and accelerator-enabled compute platforms, managing scheduling, workload placement, capacity, quotas, reservations, and utilization.
  • Create reusable Kubernetes and container platform capabilities for model training, fine-tuning, inference, and agentic workloads.
  • Develop high-performance storage, networking, and data movement for distributed AI workloads.
  • Establish observability and FinOps controls for telemetry, accelerator usage, cost attribution, anomaly detection, performance tuning, and capacity forecasting.
  • Work with AI engineering, security, risk, and platform teams on tenant isolation, access controls, secrets, supply-chain safeguards, and operational readiness.

आवश्यकताएँ

  • Experience designing infrastructure for AI agents, including runtimes, orchestration frameworks, tool integrations, asynchronous execution, and stateful workflows; examples include LangGraph and Semantic Kernel.
  • Experience using agentic AI tools in infrastructure engineering, platform support, or cloud operations, including reviewing AI-generated operational insights.
  • Experience checking AI-generated operational outputs and applying AI-enabled practices to infrastructure workflows.
  • Experience with Kubernetes-based AI platforms, containers, workload schedulers, and GPU or accelerator orchestration in cloud or hybrid environments.
  • Experience operating model serving or inference platforms and tuning throughput, latency, availability, and cost for production AI workloads.
  • Experience with distributed training or inference infrastructure, high-performance networking and storage, accelerator telemetry, and capacity planning.
  • Experience applying security, reliability engineering, observability, and FinOps practices to multi-tenant AI infrastructure.
  • Experience with Ansible, Puppet, Terraform, Python, shell scripting, and PowerShell.
  • Experience with servers, storage, networking, virtualization technologies, and network protocols.
  • Experience with databases such as DB2, SQL Server, Oracle, and MySQL.
  • Experience with cloud platforms such as AWS, Azure, and Google Cloud.
  • Experience with monitoring tools such as Prometheus, ElasticSearch, and Grafana.
  • Three to five years of experience in infrastructure engineering, cloud engineering, DevOps, or a related technical field, including at least two years supporting AI-enabled infrastructure, AI automation, or agentic AI technologies.
  • Bachelor’s degree in computer science, information technology, engineering, or comparable experience; an advanced degree is preferred.
  • Knowledge of application infrastructure and standards, storage management, middleware, software-defined networking, automation, and orchestration.
  • Knowledge of Agile, Scrum, Agile XP, Waterfall, or comparable platform delivery methods.
  • Knowledge of DevOps practices and tools, CI/CD pipelines, Docker, Kubernetes, and cloud technologies.
  • Knowledge of Windows and Linux administration.
  • Working knowledge of AI-assisted infrastructure automation, observability, deployment support, and infrastructure services for AI-enabled workloads.
  • Must be eligible to work for American Express in the United States; visa sponsorship is not available.

लाभ

  • Competitive base salary.
  • Bonus incentives.
  • A 6% company match on the retirement savings plan.
  • Complimentary financial coaching and financial well-being support.
  • Medical, dental, vision, life insurance, and disability coverage.
  • Flexible hybrid, onsite, or virtual work arrangements, depending on the role and business needs.
  • More than 20 weeks of paid parental leave for all parents, regardless of gender, for pregnancy, adoption, or surrogacy.
  • Complimentary access to global onsite wellness centers staffed by nurses and doctors, depending on location.
  • Free, confidential counseling through the Healthy Minds program.
  • Career development and training opportunities.

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