Senior Cloud Platform Engineer

Value Innovation Labs; Oaks (PA); On-site; USD 140,000 - 190,000; Full time

Job summary

Value Innovation Labs in Oaks, PA, seeks a Senior Cloud Platform Engineer to lead hands-on cloud infra, Kubernetes for AI agents, and multi-cloud networking. You will own IaC across environments and collaborate with security and network teams.

Requirements include 7+ years in cloud infra, 5+ years Kubernetes, 4+ years networking, and experience with at least two hyperscalers. On-site role in Oaks, PA with GPU connectivity focus.

Qualifications

• 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

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

Skills

Cloud infrastructure engineering

Kubernetes

Multi-cloud

Terraform

CI/CD pipelines

Networking

Infrastructure as Code

Security collaboration

LLM platform operations

Hybrid connectivity

Tools

Terraform

GitHub Actions

Azure DevOps

Kubernetes

Job description

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

• 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