DevOps Engineer

AnaVation•Chantilly, VA

10d•Onsite

About The Position

AnaVation is seeking a Senior DevOps Engineer to support the design, build, maintenance, and enhancement of Jenkins-based CI/CD pipelines using containerization and Kubernetes. The role supports software development and deployment across multiple environments, drives automation initiatives, and helps ensure reliable, secure, and scalable delivery of applications and machine learning solutions. The position is on-site in Chantilly, Virginia, and requires an active Top Secret clearance, eligibility for SCI access, and the ability to obtain a CI polygraph. The engineer will work with development, security, and operations teams in an Agile environment. Responsibilities include building automated delivery workflows, implementing infrastructure and security practices, supporting AI/ML and MLOps capabilities, resolving complex technical issues, and improving application reliability and performance. The position also involves technical leadership, mentoring, and documentation.

Requirements

Active Top Secret clearance with eligibility for Sensitive Compartmented Information (SCI) and ability to obtain a Counterintelligence (CI) polygraph.
Bachelor's degree in Computer Science, Information Technology, Engineering, or a related technical discipline, or equivalent experience.
Minimum 8 years of relevant professional experience.
Experience developing and supporting custom, in-house applications using modern programming languages and frameworks.
Expertise in AI, generative AI, and orchestration across multiple models and modalities, including reasoning, perception, memory, and tool execution.
Experience implementing temporal, spatial, geographic, quantitative, and computer vision AI capabilities.
Proficiency in named entity recognition (NER), contextual entity extraction and resolution, multi-step retrieval, and structured output generation with traceable source citations.
Experience designing and optimizing automated ETL pipelines, including complex data parsing, scheduling, and schema-aligned ingestion and normalization of structured and unstructured data.
Experience integrating and orchestrating vector, graph, and relational databases, with knowledge of Attribute-Based Access Control (ABAC), data provenance, and end-to-end lineage tracking.
Experience supporting air-gapped, hybrid, and on-premises environments, including locally hosted GPU servers, hyperconverged nodes, and multitenant Cross Domain Solutions (CDS).
Proficiency in container orchestration and distributed systems management using Docker and Kubernetes.
Experience developing user interfaces, backend services, and middleware using technologies such as TypeScript, React, Python, FastAPI, LanceDB, Lance Graph, PostgreSQL, and Temporal.io.
Experience integrating reasoning components, retrieval systems, databases, and AI/GenAI services into enterprise applications.

Nice To Haves

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 (e.g., AWS, Azure, Kubernetes, Jenkins, Security, or DevOps certifications).

Responsibilities

Design, build, maintain, and optimize enterprise CI/CD pipelines using Jenkins.
Develop and manage containerized deployment workflows using Docker and Kubernetes.
Automate software builds, testing, and deployments across multiple environments.
Create and maintain automation scripts using Python, Bash, PowerShell, or similar languages.
Implement and maintain cloud infrastructure using Infrastructure as Code and configuration management tools such as Terraform, CloudFormation, or Ansible.
Integrate DevSecOps practices and security controls into software delivery pipelines.
Support machine learning workflows, MLOps platforms, and AI/ML infrastructure.
Troubleshoot and resolve complex software, infrastructure, and deployment issues.
Implement monitoring, logging, and observability capabilities to support application reliability, performance, and scalability.
Collaborate with development, security, and operations teams within an Agile environment to improve delivery processes.
Maintain source control workflows using Git-based platforms such as GitHub, GitLab, or Bitbucket.
Lead technical initiatives, mentor engineers, and document infrastructure, pipelines, and operational procedures.