Opens LinkedIn
- Employment type
- Full-time
- Experience level
- Senior · 5+ years
- Posting language
- English
- Working hours
- 40 hours per week
- Seniority
- Mid-Senior level
- Application method
- Direct apply is available
Job summary
Develop and evolve DevOps services, CI/CD pipelines, and reusable AI platform services, while coaching application teams and promoting developer experience and DevOps best practices. Design, build, and operate enterprise AI platforms and scalable LLMOps/MLOps frameworks for model deployment, monitoring, versioning, evaluation, and governance.
Job details
AI Platform Engineer – DevOps, CI/CD, LLMOps & MLOps What Will You Do? Develop value-add services that integrate with the existing DevOps stack. Develop CI/CD pipelines using: GitHub Actions TypeScript Python Groovy Jenkins Coach application teams on leveraging DevOps offerings. Champion developer experience and DevOps best practices. Participate in new tool adoption, POCs, and provide recommendations. Evolve DevOps services for application teams. 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 Governance Build reusable AI services. Must-Have Skills Strong engineering capabilities across the SDLC and production-class delivery. Strong analytical, communication, ownership, and problem-solving skills. Development experience in one or more of: Java Python JavaScript / TypeScript C# C / C++ Experience with application and system design patterns. Experience with Docker or Kubernetes. Experience with Agile methodologies, including Scrum. Strong experience with CI/CD and DevOps practices. Experience with GitHub Actions and Jenkins. Knowledge of AI/GenAI platforms, LLMOps, and MLOps.
What you’ll do
Develop and evolve DevOps services, CI/CD pipelines, and reusable AI platform services, while coaching application teams and promoting developer experience and DevOps best practices. Design, build, and operate enterprise AI platforms and scalable LLMOps/MLOps frameworks for model deployment, monitoring, versioning, evaluation, and governance.
Requirements
Requires strong engineering and production delivery experience across the software development lifecycle, along with CI/CD and DevOps expertise, including GitHub Actions and Jenkins. Candidates should have programming experience in one or more listed languages, knowledge of application and system design patterns, Docker or Kubernetes experience, Agile/Scrum experience, and familiarity with AI platforms, LLMOps, and MLOps.
Listed skills
- Kubernetes · Preferred
- CI/CD · Preferred
- Docker · Preferred
- JavaScript · Preferred
- TypeScript · Preferred
- Java · Preferred
- C++ · Preferred
- Python · Preferred
Other relevant skills
Identified from the job description. Confirm important requirements above.
- DevOps
- CI/CD
- GitHub Actions
- Jenkins
- TypeScript
- Python
- Groovy
- Java
- JavaScript
- C#
- C/C++
- Docker
- Kubernetes
- LLMOps
- MLOps
- Agile and Scrum
Job areas
- Technology
- Software
- Engineering
- Data & Analytics
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