Own AI/ML platform capabilities, including data pipelines, distributed compute, MLOps, CI/CD, model deployment, monitoring, rollback, and compliance automation. Integrate multi-agent AI orchestration with platform services and external systems through APIs and MCP. Partner with platform engineers and product leaders to deliver reusable AI components. The role requires production distributed-systems experience, distributed ML and data tooling expertise, cloud container operations, and strong Python proficiency.
Overview/ Job ResponsibilitiesWe 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
- 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
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