AI Engineering Manager

10 hours ago

amravati, India beBeeDevops Full time

As a skilled AI Platform DevOps Engineer, you will be responsible for designing and operating highly available, scalable, and modular AI platforms using cutting-edge technologies. This includes building essential APIs and infrastructure to power conversational applications, AI agents, and analytics tools.Key Responsibilities:Design and implement AI pipelines with large language models, including inference pipelines, fine-tuning, caching, and evaluation.Deploy AI services on cloud platforms such as AWS, ensuring scalability and resilience while optimizing vector databases and model runtimes for cost and performance.Collaborate with engineering teams to deliver production-grade, self-healing, and performance-optimized services for AI/RAG pipelines.Requirements:A minimum of 8 years of experience as a Platform Engineer (Site Reliability / DevOps Engineer) with at least 3 years in AI/ML platform development (MLOps).Deep expertise in Python programming, with strong design and debugging skills.Ability to work independently and lead complex projects with excellent problem-solving, analytical, and communication skills.Proficiency working with cloud platforms such as AWS, GCP, or Azure and familiarity with MLOps/AI DevOps tools like MLflow or Kubeflow.Hands-on expertise with CI/CD pipelines, model observability, and incident response for AI/ML services.Preferred Qualifications:Experience implementing and optimizing platforms supporting large language model (LLM) pipelines with frameworks such as LangChain, LlamaIndex, Hugging Face Transformers.Hands-on knowledge of scaling & setting up vector DB platforms such as Qdrant for semantic search and embeddings management.Exposure to MLOps tools, Ray.io , Anyscale or other distributed orchestration & inference frameworks.Understanding of LLMOps patterns — model registry, prompt versioning, and feedback loops.

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