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Tier-1 consulting brand and hybrid mid-level role, but niche GenAI skills limit applicant pool.
Role requires Google-specific GenAI experience and vector DB/RAG skills, limiting cross-industry transferability.
Explicit years plus mandatory GCP/Vertex AI, ADK, and specialized GenAI tech stack demand strict filtering.
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Design, develop, and deploy scalable Generative AI applications and intelligent agents using Google Cloud services including Vertex AI, Gemini models, and Google Agent Development Kit (ADK).
Integrate AI agents with enterprise systems, develop orchestration workflows for autonomous agents, and implement Retrieval-Augmented Generation (RAG) solutions using vector databases.
Lead optimization of AI models and agents for performance and reliability; contribute to CI/CD pipelines and infrastructure deployment on Google Cloud Platform.
4-8 years of experience in software engineering, cloud application development, or AI/ML solutions.
Hands-on experience with Google Cloud Platform (GCP) services, especially Vertex AI, Gemini models, and Google ADK.
Proficiency in Python and experience with REST APIs, microservices, and cloud-native technologies (Cloud Run, GKE, Pub/Sub, Cloud Functions, BigQuery, Cloud Storage).
Experience with implementing RAG architectures using vector databases and knowledge of CI/CD, Git, Docker, and Kubernetes.
Experienced in building and deploying enterprise-grade AI applications with deep familiarity in Google Cloud AI ecosystems (Vertex AI, Gemini, ADK).
Skilled in developing AI agent orchestration and prompt engineering tailored to business use cases.
Able to collaborate with stakeholders to translate requirements into scalable, secure AI solutions and contribute to operational excellence through monitoring and optimization.