DevOps Engineer

Required Qualifications:

• Active Top Secret (TS) 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.

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

Additional information