🚀 Hiring: Senior Cloud Platform Engineer – Multi-Cloud & Hybrid Infrastructure

📍 Location: Oaks, PA — Hybrid (3 Days Onsite)

🤖 Platform: Agentic AI Platform | Financial Services

🎯 Experience: 9+ Years Overall | 7+ Years Hands-on Cloud Infrastructure Engineering

We are looking for a deeply hands-on Senior Cloud Platform Engineer with strong multi-cloud, hybrid infrastructure, Kubernetes, networking, identity, and Infrastructure-as-Code experience to support an enterprise Agentic AI Platform in the financial services industry.

Key Responsibilities

• Build and operate production Kubernetes runtimes for AI agents

• Design and implement cross-cloud networking, VPC/VNet peering, private endpoints, private DNS, NAT, and egress controls

• Establish runtime patterns across multiple hyperscalers

• Deliver private connectivity between cloud and on-premises infrastructure, including GPU environments

• Build infrastructure for AI workloads, including container registries, secrets, key management, service-to-service identity, inference endpoints, capacity, and quotas

• Establish secure connectivity for third-party and self-hosted services

• Own Terraform-based Infrastructure-as-Code, including modules, state management, and multi-environment promotion

• Collaborate with security, network, and infrastructure teams on enterprise changes and compliance requirements

• Create topology documentation, architecture decision records, and operational runbooks

Must Have

• 7+ years of hands-on cloud infrastructure engineering

• Production experience with at least two major hyperscalers: Azure, AWS, or Google Cloud

• 5+ years of production Kubernetes experience, including self-operated/unmanaged clusters

• 4+ years of enterprise cloud networking

• 3+ years of hybrid cloud and on-premises connectivity

• 3+ years integrating third-party/self-hosted services into enterprise networks

• 4+ years of Terraform or equivalent Infrastructure-as-Code

• 3+ years building infrastructure for AI or data-intensive workloads

• Working knowledge of Azure AI Foundry, Azure OpenAI, AWS Bedrock, Google Vertex AI, or equivalent

• 2+ years building CI/CD pipelines using GitHub Actions, Azure DevOps, or equivalent

• Working knowledge of LLM platform operations, including model endpoints, token throughput, quotas, rate limits, and inference cost

Preferred

• Multi-cloud certifications

• CKA or comparable Kubernetes expertise

• Self-hosted or GPU-based inference infrastructure experience

• Financial services or regulated-industry experience

• Service mesh, Private Link, or Zero Trust networking experience

• OpenTelemetry or enterprise observability experience

• AI gateway or model-routing experience

If you are interested and meet the requirements, please DM me or share your updated resume.

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