AI DevOps Engineer

About the Role

As an AI DevOps Engineer at Technoidentity, you'll be responsible for building, deploying, and managing AI-powered applications, LLM solutions, and cloud-native platforms. This role requires a strong understanding of AI, Cloud, DevOps, and Automation, with a focus on ensuring reliability, scalability, security, and observability.

You'll work closely with engineering teams to develop and deploy AI/ML and Generative AI solutions using Python, build applications leveraging LLMs, RAG, and AI agents, and create and maintain CI/CD pipelines for AI applications.

Key Responsibilities

• Develop and deploy AI/ML and Generative AI solutions using Python.
• Build applications leveraging LLMs, RAG, and AI agents.
• Create and maintain CI/CD pipelines for AI applications.
• Deploy and manage workloads using Docker and Kubernetes.
• Support cloud platforms (AWS, Azure, or GCP).
• Implement Infrastructure as Code (Terraform) and automation workflows.
• Monitor applications using observability tools such as Prometheus, Grafana, and logging platforms.

Skills & Qualifications

• Python programming (mandatory).
• Understanding of Machine Learning, LLMs, Prompt Engineering, and RAG.
• Experience with OpenAI, LangChain, LlamaIndex, or Hugging Face.
• Docker, Kubernetes, Git, and CI/CD tools.
• AWS, Azure, or GCP.
• PostgreSQL; MongoDB and Vector Databases are a plus.
• Basic knowledge of MLOps, Terraform, and workflow orchestration tools (Airflow/Temporal).
• Familiarity with observability and monitoring tools.
• Bachelor's degree in Computer Science, AI, Data Science, IT, or related field.
• 0–3 years of experience in AI/ML, Software Engineering, Cloud, DevOps, or related areas.

What You'll Learn

As an AI DevOps Engineer at Technoidentity, you'll have the opportunity to learn and grow in a dynamic and innovative environment. You'll gain hands-on experience with AI, Cloud, DevOps, and Automation, and develop skills in building, deploying, and managing AI-powered applications and cloud-native platforms.

You'll work closely with experienced engineers and learn from their expertise, and contribute to the development of MLOps practices, AI accelerators, and reusable frameworks.

Resume Tip

When applying for this role, make sure to highlight your experience with Python programming, Machine Learning, and DevOps. Emphasize your understanding of cloud platforms, such as AWS, Azure, or GCP, and your experience with Docker, Kubernetes, and CI/CD tools.

Also, be sure to mention any relevant certifications or training programs you've completed, such as those related to AI, Machine Learning, or DevOps.