Location: Chantilly, VA
Security Clearance: Active TS or higher [Required]
Job Type: Full-Time
Target Salary Range*: $113,000 - $160,000
*This represents the potential salary range for this position depending on education level, years of experience and/or certifications in addition to other position specific requirements which may impact salary
Position Overview
The Senior DevOps Engineer designs, builds, maintains, and enhances Jenkins-based CI/CD pipelines using containerization and Kubernetes technologies. This role supports software development and deployment across multiple environments, drives automation, and ensures reliable, secure, and scalable delivery of applications and machine learning solutions. The position requires strong analytical and problem-solving skills, independent work, and effective collaboration with cross-functional stakeholders.
Key Responsibilities
CI/CD Pipeline Engineering
- Design, build, maintain, and enhance Jenkins-based CI/CD pipelines.
- Support automated testing and software deployment across multiple environments.
Containerization and Automation
- Use containerization and Kubernetes technologies to support application delivery.
- Drive scripting and automation initiatives supporting development and deployment activities.
Delivery Reliability and Troubleshooting
- Ensure reliable, secure, and scalable delivery of applications and machine learning solutions.
- Troubleshoot complex software, infrastructure, and deployment issues.
Cross-Functional Collaboration
- Collaborate with cross-functional stakeholders to support software development and deployment activities.
Qualifications
Education
- Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related technical discipline, or equivalent experience.
Experience
- Minimum of 8 years of relevant professional experience.
- Demonstrated experience designing and supporting enterprise CI/CD pipelines using Jenkins.
- Experience with containerization technologies, including Docker and Kubernetes.
- Experience supporting automated testing and software deployment across multiple environments.
- Strong scripting and automation experience using Python, Bash, PowerShell, or similar languages.
- Experience with Agile development methodologies and DevOps practices.
- Experience troubleshooting complex software, infrastructure, and deployment issues.
Skills
- Knowledge of cloud platforms, infrastructure automation, and configuration management tools.
- Strong analytical and problem-solving skills.
- Ability to work independently and collaborate effectively with cross-functional stakeholders.
- Strong written and verbal communication skills.
- Technical capabilities supporting an in-house, custom-developed application.
Advanced AI, GenAI, and Multimodel Engineering
- Multimodel and multimodal orchestration involving reasoning, perception, memory, and tool execution.
- Temporal, spatial, geographic, quantitative, and computer vision AI implementation.
- Named entity recognition (NER), contextual entity extraction, and entity resolution.
- Multistep retrieval and structured output generation.
- Complex data parsing and streamlined ingestion.
- Detailed source citation and traceable analytic outputs.
Data Architecture and ETL
- Vector, graph, and multiple database orchestration.
- Automated extract, transform, and load (ETL) pipeline creation, scheduling, and optimization.
- Attribute-based access control (ABAC) at the data layer.
- Data provenance and end-to-end lineage tracking.
- Schema-aligned ingestion and normalization of diverse structured and unstructured data.
Enterprise Infrastructure and Cross-Domain Solutions
- Air-gapped, hybrid, and on-premises operational environments.
- Container orchestration and distributed systems management using Kubernetes.
- Locally hosted GPU servers and hyperconverged nodes.
- Multitenant cross-domain solutions (CDS).
Application Development and Integration
- UI, backend, and middleware engineering using TypeScript, React, Python, FastAPI, LanceDB, Lance Graph, PostgreSQL, Temporal.io, Docker, and Kubernetes.
- Integration of reasoning components, retrieval systems, databases, and AI/GenAI services.
- Use of modern programming languages and frameworks.
Preferred Qualifications
- Experience implementing DevSecOps and secure software delivery practices.
- Experience supporting machine learning workflows, MLOps platforms, or AI/ML infrastructure.
- Knowledge of infrastructure as code tools such as Terraform, CloudFormation, or Ansible.
- Experience with source control platforms such as Git, GitHub, GitLab, or Bitbucket.
- Familiarity with monitoring, logging, and observability platforms.
- Experience leading technical initiatives and mentoring engineering teams.
- Relevant industry certifications, such as AWS, Azure, Kubernetes, Jenkins, security, or DevOps certifications.Top of FormBottom of Form
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