Cloud-Native Software Engineer – Kubernetes & Microservices

Peraton•Laurel, MD

8h•$176,000 - $282,000

About The Position

Peraton is seeking a Cloud-Native Software Engineer to research, develop, evaluate, and demonstrate concepts, technologies, and capabilities that satisfy customer research requirements. The role designs, implements, and optimizes highly available cloud-native applications and infrastructure, using Kubernetes and modern cloud providers to orchestrate containerized microservices at scale. The engineer develops resilient, scalable, and cost-efficient cloud architectures; builds APIs and microservices; deploys containerized applications; automates cloud resource management; and creates data-driven dashboards. The role also orchestrates services and distributed data pipelines, builds and maintains CI/CD pipelines, implements testing strategies, monitors production systems, and works with data architects, DevOps teams, and product managers. Clear documentation of architecture, deployment workflows, and operational procedures is expected. An active TS/SCI clearance with current polygraph is required. The position requires eight years of software development or engineering experience and a bachelor's degree in computer science or a related technical field, though four additional years of experience may substitute for the degree. At least one listed cloud developer certification is also required.

Requirements

Active TS/SCI clearance with current polygraph.
Eight years of software development or engineering experience, including requirements analysis, software development, installation, integration, evaluation, enhancement, maintenance, testing, and problem diagnosis and resolution.
Bachelor's degree in computer science or a related technical field; four additional years of software development or engineering experience may substitute for the degree.
At least one of the following certifications: AWS Certified Developer-Associate, AWS DevOps Engineer Professional, Certified Kubernetes Application Developer (CKAD), or Elastic Certified Engineer.
Strong proficiency in Java (Spring Boot) or Python.
Hands-on experience with cloud platforms, preferably AWS.
Solid understanding of web application frameworks and microservice architecture.
Experience building and managing data processing pipelines.
Excellent analytical, communication, and collaboration skills.
Experience developing RESTful APIs using Java (Spring Boot) or Python.
Knowledge of Infrastructure as Code and proficiency with Terraform or AWS CloudFormation.
Understanding of stateful and stateless services and application architecture.
Deep understanding of Kubernetes internals, including Pods, Services, Namespaces, and resource management.

Nice To Haves

Experience with Kubernetes Operators and Custom Resource Definitions (CRDs).
Experience with distributed streaming platforms such as Kafka and graph databases such as Neo4j.
Experience with cloud monitoring and observability tools such as Prometheus, Grafana, or the ELK stack.
Experience with big data processing frameworks such as Apache Spark.
Experience deploying applications in a cloud environment.
Experience developing and deploying data-driven analytics, event-driven analytics, and analytics orchestrated through rules engines.
Experience developing and deploying analytics involving foreign-language processing or multimedia technologies.

Responsibilities

Design and implement resilient, scalable, and cost-efficient cloud-native architectures.
Develop and maintain RESTful APIs and microservices using Java (Spring Boot) or Python.
Build, deploy, and manage Docker-based containerized applications, with attention to image layering, security, and performance.
Use Infrastructure as Code to automate provisioning, configuration, and management of cloud resources.
Create interactive, data-driven dashboards and visualization tools using frameworks such as React or Solid.
Orchestrate services in Kubernetes, including deployments, ingress controllers, service meshes, and stateful workloads.
Design and implement distributed data pipelines to ingest, process, and store high-volume data efficiently.
Maintain data flow among cloud storage, microservices, and application layers while supporting high availability.
Build and maintain automated CI/CD pipelines for reliable software delivery.
Implement unit, integration, and cloud-readiness testing strategies.
Monitor system health and performance and identify and resolve production bottlenecks.
Collaborate with data architects, DevOps teams, and product managers to align technical solutions with business objectives.
Document architectural patterns, deployment workflows, and operational procedures.
Conduct software development and engineering activities including requirements analysis, installation, integration, evaluation, enhancement, maintenance, testing, and problem diagnosis and resolution.