Senior AI/ML Platform Engineer
Location not identified
- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
- Not stated
What you’ll work on
Full postingBuild data pipelines for model training and real-time digital twin event streams
Automate MLOps and CI/CD for AI workloads, including monitoring and rollback
Integrate multi-agent AI orchestration with platform services via APIs and MCP
Build automated control validation and evidence generation into the pipeline
Turn AI capabilities into reusable components with platform engineers and product leads
From the employer’s posting
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
All qualificationsCore experience
- Bachelor's degree in Computer Science or a related technical field, or equivalent practical experience
Qualification wording
Bachelor's degree in Computer Science or a related technical field, or equivalent practical experience
Education & alternatives
Minimum Qualifications - Bachelor's degree in Computer Science or a related technical field, or equivalent practical experience
Tools in this posting
- Python
- AWS
- Kafka
- Kubernetes
- Spark
- Airflow
Source — Tool mentions in context
- 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
- 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
- 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)
Posting record
Report an errorActively hiringFirst seen by us 1 day ago, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Oct 29, 2026 · 1 day ago
- Recorded sightings
- 1
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Your next step
- Have your resume and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
- Ask the employer about the pay range before committing time to the process.
Complete your application on careers-entarian.icims.com. The employer’s form will show what is required.
Already applied? Track this application
Job description
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
- 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
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
Location not supplied.
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
See how this role fits your experience
Add your resume to compare the role’s scope, tools and requirements with your experience.