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Platform Engineer

NALEJ

Location
Hybrid (Arlington, Virginia)
Employment
Full-time
Level
Mid Level
Posted 2 weeks ago

About the role

NALEJ is building NALEJ OS, an AI-native enterprise open-source developer platform covering the full software lifecycle from cloud to edge. The Platform Engineer role involves designing and operating multi-cluster Kubernetes infrastructure, automating delivery pipelines, and developing AI-driven workflows for defense and commercial customers.

Skills

Kubernetes Infrastructure as Code Terraform Go Python TypeScript CI/CD GitOps Service Mesh Cloud Infrastructure Zero Trust Observability AI Agents Networking Security Automation

Full job details

Job Description

Platform Engineer

 

Location: Ballston, VA

 

About NALEJ

 

NALEJ is building NALEJ OS, an AI-native, enterprise open-source developer platform for what we call the three D's: develop, deploy, and day 2 operations. It covers the whole software lifecycle on one platform, from cloud to edge: teams write code, ship it, and run it in production. We build dual-use technology across DevSecOps, DataSecOps, AI/ML Ops, Cyber Ops, and Network Ops for defense and commercial customers. We deliver it as SaaS, PaaS, IaaS, hybrid, and air-gapped deployments. Security is built in, including secure edge networks and compliance with IL4–IL6, SAP, MOSA, NIST, and Zero Trust standards.

 

About the team

 

The platform team builds and operates NALEJ OS, a production multi-cluster Kubernetes platform that serves multiple customer tenants. We own the full stack: cloud infrastructure, clusters, the service mesh, GitOps delivery, and the web applications tenants use every day.

 

We're an AI-first startup, and we build that way. Every engineer works with AI agents every day, using context files, custom agents, and shared memory tuned to our platform. You'll work with the newest tools as they come out. You'll build AI workflows that automate work people used to do by hand. You'll also ship entire features yourself, with agents working alongside you. Our team is small, so good ideas move from conversation to production fast, and nobody waits for permission to own something.

 

We're looking for generalists. In one day you might write infrastructure code in the morning, debug cross-cluster routing at lunch, and build an agent workflow before you log off. Depth in one area is great, but the job is ownership across all of them, and there's plenty of room to grow into whatever interests you most.

 

What you'll do

 

Infrastructure and clusters

  • Design, build, and operate cloud infrastructure as code across multiple accounts and environments.
  • Run multi-cluster Kubernetes in production. This covers cluster and node lifecycle, upgrades, access control, admission policy, and custom resources.
  • Automate environment creation end to end, so standing up a new customer environment takes as little human involvement as possible.

 

Delivery

  • Own the path from commit to production: CI pipelines, image builds, rendered configuration, and GitOps sync.
  • Build safe promotion between environments, including progressive delivery with automated rollback driven by metrics.
  • Build AI-driven workflows that take over the release and promotion work engineers still do by hand.

 

Networking, security, and identity

  • Operate the service mesh, including cross-cluster routing, mutual TLS, and traffic isolation between tenants.
  • Build zero-trust controls into the platform: policy enforcement, certificate management, workload identity, secrets management, and runtime threat detection.
  • Maintain the authentication chain that protects platform and tenant applications, from the identity provider through the auth proxy.

 

Observability and AI operations

  • Maintain metrics, logs, and alerting across every cluster.
  • Build agents that read those signals, triage problems, and propose fixes.

 

AI-powered engineering and ownership

  • Shape how the team works with AI. Design new agents, skills, and workflows, then roll them out to the rest of the team.
  • Help ship AI features into the product itself.
  • Build and improve the internal tools that make the whole team faster.
  • Take platform initiatives from design to delivery. Manage scope, dependencies, and timelines, and work with product, application, and test engineers early so new features fit the platform cleanly.

 

What you'll bring

 

Required

  • 3+ years of experience in platform, infrastructure, DevOps, or SRE work.
  • Experience with infrastructure as code using tools such as Terraform, Pulumi, Crossplane, or CloudFormation.
  • Hands-on experience with containers and Kubernetes, including deploying, operating, and debugging workloads in production.
  • Experience with at least one major cloud provider, such as AWS, Azure, or GCP.
  • Experience with CI/CD and an understanding of GitOps or other declarative delivery models.
  • Solid networking fundamentals: DNS, TLS, load balancing, and how traffic flows between services.
  • Working knowledge of modern identity and auth, including OIDC, OAuth 2.0, and JWTs.
  • Programming skills in at least one modern language. We work mostly in Go, Python, and TypeScript, and you should be willing to pick up the others.
  • Real enthusiasm for AI-assisted development and an appetite for trying new tools.
  • Strong drive and a self-starter mindset. You find problems without being told and follow through.
  • Clear written communication. You can explain a design decision and its tradeoffs to someone who wasn't in the room.

 

Preferred

  • Experience running multi-cluster or multi-tenant Kubernetes in production.
  • Experience with a service mesh such as Istio, Linkerd, or Cilium.
  • Experience with policy as code and Kubernetes security tools, such as Kyverno, OPA Gatekeeper, or Falco.
  • Experience with observability stacks, such as Prometheus, Grafana, Loki, or OpenTelemetry.
  • Experience with progressive delivery, such as canary or blue-green releases with automated analysis.
  • Experience in regulated or security-sensitive environments, such as defense, healthcare, or critical infrastructure, or with compliance frameworks such as NIST 800-53, FedRAMP, or DoD Impact Levels.
  • Experience building with LLMs, such as agent workflows, MCP servers, AI developer tooling, or AI product features.
  • Cloud or Kubernetes certifications, such as AWS Solutions Architect, CKA, or CKS.
  • A bachelor's or master's degree in computer science, engineering, or a related field, or equivalent experience.

 

What success looks like

  • You take a project from idea through architecture, implementation, and production, and you own it after launch.
  • You ship complete features on your own, with AI agents writing, testing, and reviewing code alongside you.
  • You replace a manual process with an AI workflow that runs without anyone touching it.
  • You become the go-to expert for a major part of the platform and help set its direction.
  • You help shape how the whole team builds with AI.

 

Additional requirements

  • U.S. citizenship is required.
  • This role may require the ability to obtain a Secret clearance.