Senior Cloud AI Strategist

1 day ago

Mumbai, Maharashtra, India beBeeAgile Full time ₹ 3,50,00,000 - ₹ 4,50,00,000
Job Title: Visionary AI Architect

We are seeking a visionary AI architect with a strong background in cloud architecture and deep knowledge of RAG and agentic AI patterns. This role combines strategic vision with technical depth, leading a team of engineers to implement AI-powered applications at scale.

Key Responsibilities:
  • Develop GenAI or ML solution architectures across cloud, edge, and hybrid environments.
  • Evaluate Large Language Model (LLM) applications and design observability frameworks.
  • Research and implement the latest technologies and frameworks.
  • Work with diffusion models like Stable Diffusion, MidJourney, Runway, Imagen, Veo, etc.
  • Lead design and implementation of RAG-based knowledge systems and agentic AI workflows.
  • Select and integrate enterprise-grade AI models (OpenAI, Anthropic, Mistral, LLaMA, custom fine-tuned models).
  • Drive cloud-native AI deployments leveraging AWS, Azure, and GCP AI services.
  • Architect LLMOps pipelines for scalable AI model lifecycle management.
  • Implement AI governance, risk management, and compliance frameworks for regulated industries.
  • Lead PoCs and pilots, then guide them to production-grade rollouts.
  • Optimize AI cost, performance, and security trade-offs.
  • Mentor and manage AI engineers, setting best practices for RAG, agentic, and edge AI.
Requirements:
  • 8–15 years of technology experience, with 4+ years in AI/ML and 2+ years in GenAI.
  • Proven leadership in cloud AI architectures (AWS Bedrock/SageMaker, Azure OpenAI, GCP Vertex AI).
  • Strong expertise in RAG architectures, embeddings, and semantic search.
  • Experience in agentic AI frameworks (LangGraph Agents, Autogen, CrewAI, OpenAI/Google Agent SDK).
  • Advanced knowledge of vector stores, distributed search, and multi-modal AI.
  • Proficiency in edge AI deployments and low-latency AI inference optimization.
  • Expertise in cloud networking, identity, and security for AI workloads.
  • Strong understanding of AI product lifecycle, from ideation to production.
  • Excellent stakeholder management and team leadership skills.

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