• 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

• 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

• Bachelor's degree in Computer Science or a related technical field, or equivalent practical experience

8+ years software engineering experience, distributed systems, ML/data engineering tools (Spark, Kafka, NiFi, Airflow), containerized workloads on cloud (AWS, Kubernetes, OpenShift), Python, CI/CD automation, Bachelor's in CS or equivalent.

Key Responsibilities

• engineering data pipelines
• automating MLOps
• integrating AI orchestration

Skills & Tools

Apache Spark, MLlib, Kafka, NiFi, Airflow, AWS, Kubernetes, EKS, Red Hat OpenShift, Python, CI/CD

Job Details

• Category: Software Development
• Seniority: Senior Level
• Commitment: Full Time
• Workplace: Remote — United States
• Languages: English

Benefits

• 401k matching
• Retirement plan

About Entarian

A technology company building AI and machine learning platforms. — Industry: Information Technology