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Tier-1 brand, metro context, and broad in-demand AI/LLM skillset create high competition.
Requires specialized LLM, RAG, and vector-database expertise, limiting cross-industry transferability.
Many mandatory specialized GCP and LLM technologies required without explicit years, making filters moderately strict.
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Design and architect end-to-end AI and Generative AI solutions leveraging Google Cloud Platform services including Vertex AI, Gemini Models, BigQuery, and Kubernetes.
Define and enforce enterprise architecture standards focusing on security, governance, scalability, and responsible AI compliance.
Lead technical workshops, conduct solution discovery, guide development and DevOps teams, and manage proof of concepts (PoCs), MVPs, and production deployments for Agentic AI solutions involving LLMs, RAG architectures, vector databases, and multi-agent designs.
Proven experience designing AI/GenAI solutions on Google Cloud Platform with expertise in Vertex AI, GKE, Cloud Functions, IAM, and related technologies.
Experience with architectures involving RAG, vector databases (e.g., Pinecone, Weaviate, Vertex AI Vector Search), multi-agent systems, and orchestration frameworks.
Demonstrated ability to lead and deliver PoCs, MVPs, and production AI solution implementations.
Work Experience Required: Not explicitly mentioned in the JD.
Strong background in cloud-native AI/ML architecture with an emphasis on GCP services and Generative AI frameworks.
Experienced in enterprise-level solution design including security, governance, and scalability for AI systems.
Skilled in collaborating across business and technical teams to translate complex requirements into scalable, compliant AI solutions.