Salary
≈ $115k – $222k per year (Estimated)
Location
In office (United States)
Seniority
Senior · 8+ years exp
Confirmed on the employer's own hiring board on Oct 29, 2026. First seen by Alion on Oct 28, 2026.
Overview
Company
Impact
Profile match
Entarian is a US federal engineering and technology contractor headquartered in Greenbelt, Maryland, delivering satellite mission operations, network and communications, command and control, cyber defense, IT modernization and science data processing for space, defense and civilian agencies. Formed through the union of Sev1Tech and ERT, it traces its roots to 1993, has 13 offices across the US and holds ISO 9001, ISO 27001 and CMMI Level 3 certifications. It hires cybersecurity administrators, DevSecOps and cloud network engineers, UNIX system engineers, program managers, trainers, data analysts and fisheries biologists.
Overview/ Job Responsibilities
We are hiring a Senior AI/ML Platform Engineer to own the AI and machine learning embedded in a new and exciting platform; the data pipelines that feed models, the compute that serves them, and the automation that keeps AI workloads secure, reproducible, and compliant. You will work across the platform's layers with primary focus on the AI/ML workloads that run on them and connect them.What You'll Do
- Engineer the data pipelines that feed AI workloads - ingestion, transformation, and serving for model training and real-time digital twin event streams
- Automate MLOps and CI/CD for AI workloads: reproducible builds, test automation, deployment, monitoring, and rollback
- Integrate multi-agent AI orchestration with platform services and external systems through APIs and agent-tool protocols such as MCP
- Build compliance into the pipeline - automated control validation and evidence generation that shorten ATO cycles
- Partner with platform engineers and product leads to turn AI capabilities into reusable components
What You'll Bring
- 8+ years of professional software engineering experience, including designing and operating production distributed systems
- Hands-on experience with distributed ML and data engineering tooling (for example, Apache Spark/MLlib, Kafka, NiFi, or Airflow)
- Experience deploying and operating containerized workloads on a major cloud platform (AWS preferred; Kubernetes/EKS or Red Hat OpenShift a plus)
- Proficiency in Python
- Experience with CI/CD pipeline automation and pipeline-as-code
Minimum Qualifications
- Bachelor's degree in Computer Science or a related technical field, or equivalent practical experience
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