Principal Cloud & Platform Architect - AI-First Hybrid

Leidos Inc

Egg Harbor Township (NJ)

Hybrid

USD 131,000 - 237,000

Full time

6 days ago

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Job summary

Leidos is seeking a Principal Cloud & Platform Architect to join the Air Traffic Business Area, supporting the L-CAP platform. The role involves designing a hybrid cloud data mesh and overseeing platform services, IaC governance, and reliability for mission-critical systems.

Requires 12+ years in cloud/platform engineering, FedRAMP experience, and US citizenship. Hybrid work model with 3 onsite and 2 remote days, multiple U.S. locations, and a Public Trust clearance path.

Qualifications

Bachelor's degree with 12+ years of cloud and platform engineering experience.
Expert-level cloud architecture experience with AWS or Azure GovCloud.
Production Kubernetes experience at scale (100+ nodes).
Deep Terraform/IaC expertise for enterprise infrastructure management.
Platform engineering leadership for large development organizations.

Responsibilities

Design the hybrid cloud architecture spanning on-premises and cloud environments.
Define Kubernetes orchestration strategy for containerized workloads at scale.
Establish Infrastructure-as-Code governance using Terraform.
Architect FedRAMP-compliant platform designs across multiple environments.
Design and govern CI/CD platform services for engineering teams.
Lead capacity planning and infrastructure cost modeling.
Define platform reliability standards including SLOs and SLIs.
Design multi-environment deployment strategy (dev, test, staging, production).
Oversee container orchestration patterns and service mesh architecture.
Drive cloud cost optimization and FinOps practices.
Design platform architecture to host safety-critical ATC applications with deterministic performance characteristics.
Ensure operational resilience and failover capabilities for distributed real-time ATC services across hybrid cloud deployments.
Define platform requirements for deterministic distributed services including latency guarantees and predictable resource allocation.
Champion an AI-first engineering culture by identifying and applying AI-assisted development capabilities, automation, and emerging software engineering practices that improve developer productivity, code quality, testing, and delivery.