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AI ML Architect
AI ML ArchitectConfidential • Bengaluru / Bangalore
AI ML Architect

AI ML Architect

Confidential • Bengaluru / Bangalore
24 days ago
Job description

Your Role :

  • Define and own the end-to-end architecture for enterprise-scale GenAI and AI solutions.
  • Design reference architectures, reusable patterns, and best practices for integrating GenAI into business applications.
  • Collaborate with domain experts, data scientists, and developers to align business needs with scalable AI architectures.
  • Select and evaluate LLMs, vector databases, and orchestration frameworks based on performance, compliance, and cost.
  • Architect RAG pipelines, agentic workflows, and multi-agent ecosystems for production-grade implementations.
  • Ensure security, privacy, and governance frameworks are embedded into AI systems from inception.
  • Drive adoption of cloud-native AI services (Azure OpenAI, AWS Bedrock) and ensure scalability and performance optimization.
  • Guide teams in model lifecycle management, including deployment, monitoring, retraining, and drift handling (MLOps).
  • Evaluate and recommend tools, frameworks, and protocols such as MCP, LangChain, and LangGraph for interoperability.
  • Stay updated with advancements in GenAI, AI regulations, and enterprise adoption trends, translating insights into strategic roadmaps.

Required Skills and Qualifications :

  • Bachelor's or Master's degree in Computer Science, Statistics, Engineering, or a related field.
  • Proven experience as an AI / ML / GenAI Architect designing and implementing large-scale AI / ML systems.
  • Deep expertise in Python and ML / DL frameworks like PyTorch and TensorFlow.
  • Strong understanding of LLM architectures, fine-tuning methods (LoRA, PEFT, adapters), and deployment strategies.
  • Expertise in RAG pipelines, embeddings, and vector databases such as Elastic, Pinecone, and Milvus.
  • Familiarity with agentic GenAI systems including LangChain, LlamaIndex, AutoGen, Crew.ai, and LangGraph.
  • Knowledge of Model Context Protocol (MCP) for secure GenAI integrations.
  • Experience with cloud-native architecture (AWS, Azure) and container orchestration (Docker, Kubernetes).
  • Strong understanding of MLOps principles including CI / CD for ML, observability, retraining, and governance.
  • Ability to bridge business and technology, communicating complex AI strategies effectively to stakeholders.
  • Deep understanding of Responsible AI principles and integration of governance and ethical frameworks into solutions.
  • Bonus : Experience in enterprise-scale AI adoption within the Telecom industry.
  • Skills Required

    Python, Pytorch, Tensorflow

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