AI Devops Engineer

Technoidentity

Hyderabad

On-site

INR 600,000 - 900,000

Full time

14 days+
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Job summary

Technoidentity is hiring an AI DevOps Engineer with 0–3 years of experience to design, deploy, and manage AI-powered applications and cloud-native platforms. You will work on LLM-based solutions, RAG, and AI agents, building robust CI/CD pipelines and provisioning infrastructure with Terraform.

You will collaborate closely with engineering teams to ensure reliability, security, and observability across AWS, Azure, or GCP deployments, while contributing to MLOps practices and scalable AI

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
  • PostgreSQL; MongoDB and Vector Databases are a plus
  • Basic knowledge of MLOps, Terraform, and workflow orchestration tools (Airflow/Temporal)
  • Observability and monitoring tools familiarity

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.
  • Collaborate with engineering teams to ensure system reliability, performance, and security.
  • Contribute to MLOps practices, AI accelerators, and reusable frameworks.

Skills

Python
LLMs
Prompt Engineering
RAG

Education

Bachelor's degree in Computer Science, AI, Data Science, IT, or related field

Tools

Docker
Kubernetes
Git
CI/CD tools
Terraform
Prometheus
Grafana

Job description

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Job Description

At Technoidentity, we're a Data & AI product engineering company with over 15 years of expertise in building durable digital products, intelligent enterprise solutions, and scalable Data & AI platforms. As we continue expanding globally, it's the perfect time to join our team of tech innovators and make a lasting impact.

What’s in it for You?

We are looking for an AI DevOps Engineer with 0–3 years of experience who is passionate about AI, Cloud, DevOps, and Automation. The role involves building, deploying, and managing AI-powered applications, LLM solutions, and cloud-native platforms while ensuring reliability, scalability, security, and observability.

What Will You Be Doing?

  • 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.
  • Collaborate with engineering teams to ensure system reliability, performance, and security.
  • Contribute to MLOps practices, AI accelerators, and reusable frameworks.
Requirements

What Makes You the Perfect Fit?

  • 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
  • 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
Qualifications
  • 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
Nice to Have
  • Experience with Agentic AI frameworks
  • Knowledge of MLOps and AI platform operations
  • Exposure to enterprise-grade monitoring, reliability engineering, and security best practices
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