Senior or Lead DevOps Engineer/Sr Automation Expert

1 week ago

Bengaluru, Karnataka, India Techno Facts Solutions Full time ₹ 12,00,000 - ₹ 36,00,000 per year

Role Summary: Mandatory (Min 6 m-2 years in Gen Ai)

We are seeking a Senior or Lead DevOps Engineer with hands-on experience in automating and scaling Generative AI (GenAI) projects. This role will focus on building robust, secure, and scalable MLOps/DevOps pipelines tailored for GenAI workflows, enabling rapid development, experimentation, and deployment of large-scale AI models.

Key Responsibilities:

  • Design, build, and maintain CI/CD pipelines for GenAI model development, training, and deployment.
  • Automate provisioning and scaling of infrastructure for GenAI workloads using tools like Terraform, Ansible, or Pulumi.
  • Optimize GPU/TPU usage and monitor model performance in production environments.
  • Integrate GenAI workflows (e.g., LLM fine-tuning, embedding generation, RAG pipelines) into production-grade infrastructure.
  • Collaborate with ML Engineers, Data Scientists, and Platform Engineers to ensure reproducibility, versioning, and traceability of models and datasets.
  • Implement observability for GenAI workloads (logging, monitoring, alerting).
  • Ensure best practices around security, compliance, and cost optimization in cloud and hybrid environments.

Required Skills & Qualifications:

  • 5+ years of DevOps / MLOps experience, with at least 12 years in GenAI-focused environments.
  • Strong proficiency in automation tools: Docker, Kubernetes, Terraform, Jenkins/GitLab CI, Helm.
  • Hands-on experience with LLMs, transformer-based models, or GenAI frameworks (e.g., Hugging Face, LangChain, OpenAI, or similar).
  • Deep understanding of cloud platforms (AWS/GCP/Azure), especially AI/ML services like Sagemaker, Vertex AI, or Azure ML.
  • Experience in monitoring large-scale systems (Prometheus, Grafana, ELK).
  • Familiarity with model/version management tools (MLflow, Weights & Biases, DVC).
  • Strong scripting skills – Python, Bash, or Go.

Preferred Qualifications:

  • Experience with RAG (Retrieval-Augmented Generation) pipelines.
  • Exposure to LLMOps, prompt management tools, or GenAI orchestration platforms (e.g., LangServe, BentoML, FastAPI).
  • Experience with enterprise security standards for ML environments.

Soft Skills:

  • Strong problem-solving mindset and ownership of delivery.
  • Ability to lead infrastructure design discussions for GenAI projects.
  • Effective communicator, able to work cross-functionally across AI, data, and DevOps teams.

What You'll Get:

  • Opportunity to shape and scale GenAI infrastructure in production.
  • Work with state-of-the-art models and tools.
  • Competitive compensation, flexible working environment, and growth opportunities.

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