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Senior AI Platform DevOps Engineer
Senior AI Platform DevOps EngineerCloudely, Inc • Lucknow, IN
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Senior AI Platform DevOps Engineer

Senior AI Platform DevOps Engineer

Cloudely, Inc • Lucknow, IN
3 days ago
Job description

AI Platform DevOpes / SRE Engineer

Location : India - 100% Remote

Fulltime Permanent Position

Responsibilities / What You’ll Do

  • Platform Design and Architecture : building and operating a highly available, scalable, modular AI platform using technologies such as Qdrant, Anyscale, and Ray to support LLM orchestration, vector search, and multi-agent frameworks.
  • Core Infrastructure Development : Build essential APIs and infrastructure to power conversational applications, AI agents, and analytics tools.
  • LLM Operational Solutions : Implement workflows for Large Language Models, including inference pipelines, fine-tuning, caching, and evaluation for open-weight and hosted models.
  • Deployment & Performance Optimization : Deploy AI services on AWS with Kubernetes (EKS), Lambda, and ECS, ensuring scalability and resilience while optimizing vector databases and model runtimes for cost and performance.
  • Collaboration, Governance, & Mentorship : Partner with engineering teams, research teams to deliver production-grade, self-healing, and performance-optimized services for AI / RAG pipelines , establish governance / security standards, and mentoring junior engineers in AI infrastructure best practices & reviews.

What We’re Looking for (Minimum Qualifications) :

  • 8+ years of experience as Platform Engineer ( Site Reliability / DevOps Engineer) , with at least 3+ years in AI / ML platform development ( MLOps ).
  • Deep expertise in Python, 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, proficient in CI / CD , infrastructure as code (Terraform / CloudFormation).
  • Hands-on expertise with CI / CD pipelines, model observability, and incident response for AI / ML services.
  • Preferred Qualification :

  • Experience implementing and optimizing Platforms supporting large language model (LLM) pipelines with frameworks such as LangChain, LlamaIndex, Hugging Face Transformers, or similar.
  • Hands-on knowledge of Scaling & Setting up Vector DB platforms such as Qdrant (or other vector DBs like Pinecone, Weaviate) for semantic search and embeddings management.
  • Exposure to MLOps tools, Ray.io , Anyscale or other distributed orchestration & inference frameworks.
  • Experience with developing and deploying containerized applications using Docker and Kubernetes, including Helm charts and automated scaling.
  • Understanding of LLMOps patterns — model registry, prompt versioning, and feedback loops.
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