AI Platform Engineer with DevOps
Apptoza Inc.
Role: AI Platform Engineer with DevOps Experience - DevOps, Docker (Software), GitHub, GitHub Actions, Information Technology (IT) Infrastructure, Kubernetes, Programming Languages, Red Hat Ansible,Software Product Design, Software Product Technical Knowledge, Software GenAI, LLM
What will you do?
Develop value-add services which integrate with the existing DevOps stack
Develop CICD pipelines using GitHub Actions, TypeScript, Python, Groovy and Jenkins
Coach application teams on how to leverage DevOps offerings
Champion developer-experience and best practices in conjunction with DevOps to ensure no developer is left behind
Participate in new tool adoption, POC process and provide recommendations
Evolve DevOps services beyond current state for application teams
What do you need to succeed? Must-have:
An engineer mindset, SDLC experience with production class delivery, strong analytical mindset, communication skills, and sense of ownership / drive
Experience with application and system design patterns
Experience with Docker or Kubernetes
Experience with Agile methodologies, ie SCRUM
Design, build, and operate enterprise AI/GenAI platforms supporting Large Language Models (LLMs) and AI-powered applications.
Develop scalable LLMOps and MLOps frameworks for model deployment, monitoring, versioning, evaluation, and governance.
Build reusable AI services including:
Retrieval Augmented Generation (RAG) architectures
Embedding and Vector Search Services
AI Gateway and Inference APIs
Agentic AI Orchestration Frameworks
Nice-to-have:
Experience with Elastic Search and Kibana
Experience using DevOps CICD tools such as GitHub, GitHub Actions, Jenkins, UrbanCodeDeploy
Experience with a public cloud technology, i.e. Azure, AWS
Experience building or supporting distributed applications
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What will you do?
Develop value-add services which integrate with the existing DevOps stack
Develop CICD pipelines using GitHub Actions, TypeScript, Python, Groovy and Jenkins
Coach application teams on how to leverage DevOps offerings
Champion developer-experience and best practices in conjunction with DevOps to ensure no developer is left behind
Participate in new tool adoption, POC process and provide recommendations
Evolve DevOps services beyond current state for application teams
What do you need to succeed? Must-have:
An engineer mindset, SDLC experience with production class delivery, strong analytical mindset, communication skills, and sense of ownership / drive
Experience with application and system design patterns
Experience with Docker or Kubernetes
Experience with Agile methodologies, ie SCRUM
Design, build, and operate enterprise AI/GenAI platforms supporting Large Language Models (LLMs) and AI-powered applications.
Develop scalable LLMOps and MLOps frameworks for model deployment, monitoring, versioning, evaluation, and governance.
Build reusable AI services including:
Retrieval Augmented Generation (RAG) architectures
Embedding and Vector Search Services
AI Gateway and Inference APIs
Agentic AI Orchestration Frameworks
Nice-to-have:
Experience with Elastic Search and Kibana
Experience using DevOps CICD tools such as GitHub, GitHub Actions, Jenkins, UrbanCodeDeploy
Experience with a public cloud technology, i.e. Azure, AWS
Experience building or supporting distributed applications
#J-18808-Ljbffr
Reference: WJ-3875_13025763