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Cloud: Azure (incl. Azure AI, OpenAI, Cognitive Services), AWS (Bedrock/SageMaker), GCP (Vertex AI); containerization (Docker/Kubernetes) and service meshes.
Data & Integration: SQL, NoSQL, data warehousing concepts (fact/dimension, SCD), ETL/ELT, streaming (Kafka/Event Hubs), API design, and secure integration (OAuth2/JWT/RBAC).
LLMOps/MLOps & Automation: CI/CD for models, model registry, feature store, monitoring (tokens, drift, hallucinations), Python automation for infra and pipelines. Engineering Practices
Proficiency in Python, LangChain/LangGraph, vector DBs, and prompt/agent frameworks; strong Git, CI/CD, IaC, and Agile/Scrum delivery. Architecture Leadership
Prior ownership of complex AI solution designs, HLD/LLD, NFRs, and security/ compliance patterns; ability to mentor squads and lead design forums.
Preferred Skills
Experience designing AI gateways, MCP (Model Context Protocol) implementations, and agent registries; familiarity with metadata standards (DCAT/JSON-LD).
Exposure to enterprise AI platforms/labs and accelerators
Knowledge of infrastructure automation in DC/cloud (orchestration, provisioning) with AI workloads and GPU scheduling (K8s, NCCL, Triton).
Prior work on Microsoft Copilot Studio solutions, conversational agents, and Power Platform extensibility.
Qualifications & Certifications · B.Tech or Equivalent degree · Certifications (any subset): Azure AI Engineer/Architect, Azure OpenAI, AWS/GCP AI, Databricks ML, Kubernetes
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