Contact person: Business Client

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Location: Seattle, United States

Budget: Recommended by industry experts

Time to start: As soon as possible

Project description:
"We are looking for a Vertex AI Search Expert to implements enterprise AI search solution using Google’s Gemini models and search infrastructure for our platform (combination of social media and e-commerce).

*****Send your resume and live project you launched in order to be considered!

Key Responsibilities
- Design search architectures using Vertex AI Search for structured and unstructured data.
- Build and optimize Retrieval-Augmented Generation (RAG) workflows to ground LLM responses in enterprise data, reducing hallucinations.
- Develop data pipelines using Dataflow, BigQuery, and Cloud Storage to feed data into search indices.
- Fine-tune ranking, indexing, and relevance using features like Vector Search (Matching Engine), embeddings, and semantic understanding.
- Design "agentic" AI systems that can perform complex, multi-step tasks across data stores.
- Configure search features like autocomplete, facets, and recommendations for our e-commerce and social media.

Required Technical Skills:
- Proficiency in Google Cloud Platform (GCP) and the Vertex AI suite (Search & Conversation, Vertex AI Studio, and Model Garden).
- Mastery of customizing search functionality via APIs and SDKs.
- Strong understanding of LLMs (Gemini), prompt engineering, tokenization, and vector-based information retrieval.
- Experience with BigQuery, Cloud SQL, and SQL-based data modeling.
- Knowledge of VPC configurations, Private Service Connect, and data privacy standards (e.g., HIPAA, GDPR) for AI deployments.

Qualifications
- 3+ years in cloud solution development or AI/ML engineering, with experience in search engine principles.
- Certification (Preferred): Google Professional Machine Learning Engineer or the 2025 Vertex AI Technical" (client-provided description)