{"id":4253,"date":"2025-06-27T19:59:56","date_gmt":"2025-06-27T19:59:56","guid":{"rendered":"https:\/\/code2deploy.com\/blog\/?p=4253"},"modified":"2025-06-27T19:59:57","modified_gmt":"2025-06-27T19:59:57","slug":"the-new-ai-stack-roles-responsibilities-and-tools","status":"publish","type":"post","link":"https:\/\/code2deploy.com\/blog\/the-new-ai-stack-roles-responsibilities-and-tools\/","title":{"rendered":"The New AI Stack \u2014 Roles, Responsibilities, and Tools"},"content":{"rendered":"\n
\"mlops,dataops,devops,ml-engineer,<\/figure>\n\n\n\n
\n\n\n\n

1. Infrastructure Layer<\/strong><\/h3>\n\n\n\n

Role<\/strong>: Provision, monitor, and manage the scalable infrastructure required for model deployment and data processing.<\/p>\n\n\n\n

Roles Involved<\/strong>:<\/p>\n\n\n\n

    \n
  • DevOps Engineer<\/strong>: Automates deployment, manages cloud and container infrastructure (Kubernetes, Docker)
    <\/li>\n\n\n\n
  • MLOps Engineer<\/strong>: Manages model serving, versioning, and monitoring
    <\/li>\n\n\n\n
  • DataOps Engineer<\/strong>: Ensures reliable and reproducible data pipelines
    <\/li>\n<\/ul>\n\n\n\n
    Responsibility<\/strong><\/td>Tools \/ Tech<\/strong><\/td>Roles Involved<\/strong><\/td><\/tr>
    Compute Management<\/td>SkyPilot, Kubernetes, Ray<\/td>DevOps, MLOps<\/td><\/tr>
    Data Management<\/td>Feast, LakeFS, Airbyte<\/td>DataOps, MLOps<\/td><\/tr>
    Model Serving<\/td>vLLM, Triton, TorchServe<\/td>MLOps, DevOps<\/td><\/tr>
    Monitoring & Logging<\/td>Prometheus, Grafana, Arize<\/td>MLOps, DevOps<\/td><\/tr>
    Vector Search \/ DB<\/td>FAISS, Milvus, Qdrant<\/td>MLOps, LLM Engineer<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n
    \n\n\n\n

    2. Model Development Layer<\/strong><\/h3>\n\n\n\n

    Role<\/strong>: Build, fine-tune, and evaluate ML\/LLM models.<\/p>\n\n\n\n

    Roles Involved<\/strong>:<\/p>\n\n\n\n

      \n
    • ML Engineer<\/strong>: Core model development and experimentation
      <\/li>\n\n\n\n
    • LLM Engineer \/ Researcher<\/strong>: Works on large models, prompt tuning, and embeddings
      <\/li>\n\n\n\n
    • MLOps Engineer<\/strong>: Tracks experiments, streamlines training-to-deploy flow
      <\/li>\n<\/ul>\n\n\n\n
      Responsibility<\/strong><\/td>Tools \/ Tech<\/strong><\/td>Roles Involved<\/strong><\/td><\/tr>
      Dataset Engineering<\/td>Label Studio, Snorkel, cleanlab<\/td>ML Engineer, DataOps<\/td><\/tr>
      Modeling & Training<\/td>Transformers, PyTorch, Lightning<\/td>ML Engineer, LLM Engineer<\/td><\/tr>
      Inference Optimization<\/td>ONNX, TensorRT, GGUF, vLLM<\/td>MLOps, ML Engineer<\/td><\/tr>
      Evaluation<\/td>RAGAS, TruLens, EvalLM, Promptfoo<\/td>ML Engineer, LLM Engineer<\/td><\/tr>
      RAG\/LLM Interface Dev<\/td>LangChain, LlamaIndex, Haystack<\/td>LLM Engineer, MLOps<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n
      \n\n\n\n

      3. Application Layer<\/strong><\/h3>\n\n\n\n

      Role<\/strong>: Deliver usable AI experiences via APIs, UIs, agents, and interfaces.<\/p>\n\n\n\n

      Roles Involved<\/strong>:<\/p>\n\n\n\n

        \n
      • AI Application Developer<\/strong>: Builds interfaces and workflows
        <\/li>\n\n\n\n
      • Prompt Engineer \/ LLM Engineer<\/strong>: Refines model interaction
        <\/li>\n\n\n\n
      • Full-Stack Developer<\/strong>: Integrates front-end + API with AI
        <\/li>\n<\/ul>\n\n\n\n
        Responsibility<\/strong><\/td>Tools \/ Tech<\/strong><\/td>Roles Involved<\/strong><\/td><\/tr>
        Prompt Engineering<\/td>PromptLayer, Promptfoo, OpenAI Evals<\/td>LLM Engineer, Prompt Eng.<\/td><\/tr>
        Agentic Orchestration<\/td>LangChain, CrewAI, DSPy, Flowise<\/td>LLM Engineer, AI Developer<\/td><\/tr>
        UI \/ API Development<\/td>FastAPI, Streamlit, Gradio, Next.js<\/td>Full-stack Dev, AI Dev<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n
        \n\n\n\n

        Cross-Cutting Functions<\/strong><\/h2>\n\n\n\n
        Task<\/strong><\/td>Tools \/ Tech<\/strong><\/td>Roles Involved<\/strong><\/td><\/tr>
        Experiment Tracking<\/td>MLflow, Weights & Biases<\/td>MLOps, ML Engineer<\/td><\/tr>
        Model\/Data Versioning<\/td>DVC, LakeFS, Feast<\/td>MLOps, DataOps<\/td><\/tr>
        CI\/CD Automation<\/td>GitHub Actions, KubeFlow, DVC<\/td>MLOps, DevOps<\/td><\/tr>
        Guardrails & Testing<\/td>Guardrails AI, Rebuff<\/td>Prompt Engineer, QA, MLOps<\/td><\/tr><\/tbody><\/table><\/figure>\n","protected":false},"excerpt":{"rendered":"

        1. Infrastructure Layer Role: Provision, monitor, and manage the scalable infrastructure required for model deployment and data processing. Roles Involved: Responsibility Tools \/ Tech Roles Involved Compute Management SkyPilot, Kubernetes, Ray DevOps, MLOps Data Management Feast, LakeFS, Airbyte DataOps, MLOps Model Serving vLLM, Triton, TorchServe MLOps, DevOps Monitoring & Logging Prometheus, Grafana, Arize MLOps, DevOps […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[609,839,842,837,840,838,836,841],"tags":[846,858,847,848,843,851,854,845,844,767,853,856,855,849,852,850,857],"class_list":["post-4253","post","type-post","status-publish","format-standard","hentry","category-ai","category-aiops","category-app-developer","category-dataops","category-llm-engineer","category-ml-engineer","category-mlops-ai","category-prompt-engineer","tag-aiops","tag-app-dev-fastapi","tag-compute-skypilot","tag-data-mgmt-feast","tag-dataops","tag-dataset-snorkel","tag-evaluation-ragas","tag-llm-engineer","tag-ml-engineer","tag-mlops","tag-optimize-onnx","tag-prompt-eng-promptlayer","tag-rag-langchain","tag-serving-vllm","tag-training-pytorch","tag-vector-db","tag-workflows-crewai"],"yoast_head":"\nThe New AI Stack \u2014 Roles, Responsibilities, and Tools - code2deploy.com<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/code2deploy.com\/blog\/the-new-ai-stack-roles-responsibilities-and-tools\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"The New AI Stack \u2014 Roles, Responsibilities, and Tools - code2deploy.com\" \/>\n<meta property=\"og:description\" content=\"1. Infrastructure Layer Role: Provision, monitor, and manage the scalable infrastructure required for model deployment and data processing. 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