Overview:

We are looking for a Google Vertex AI specialist with strong experience in implementing and optimizing AI-powered search solutions for e-commerce platforms. The ideal consultant will help us design, configure, and deploy Vertex AI Search to deliver accurate, fast, and personalized product search experiences on our website.

Key Responsibilities:

1. Implement and configure Google Vertex AI Search for an e-commerce website.
2. Build and optimize product search experiences, including relevance tuning, ranking, filtering, and autocomplete.
3. Integrate Vertex AI Search with existing product catalog, CMS, and backend systems.
4. Set up real-time or scheduled data ingestion from product databases/feeds.
5. Enable personalized search results using user behavior signals where applicable.
6. Work closely with engineering, product, and UX teams to define search requirements.
7. Improve search performance through continuous fine-tuning, A/B testing, and relevance evaluation.
8. Troubleshoot issues related to search quality, indexing, latency, or API integrations.
9. Provide best practices for scalable, secure, and high-performance search deployment.

Required Skills & Experience:

1. Strong hands-on experience with Google Cloud Platform (GCP), especially Vertex AI Search (formerly Retail Search).
2. Experience implementing e-commerce search, product discovery, or recommendation systems.
3. Knowledge of search concepts: indexing, ranking, vector search, embeddings, ML-based relevance, synonyms, facets, filters, and search analytics.
4. Experience with APIs, JSON, REST, and integrating search with web applications.
5. Familiarity with BigQuery, Cloud Storage, Cloud Functions, Pub/Sub, or other GCP services.
6. Ability to work with structured and unstructured product data.
7. Understanding of UX patterns for search and product discovery.
8. Strong problem-solving skills and ability to work independently.

Preferred Qualifications:

1. Prior experience implementing Vertex AI Search for retail or e-commerce clients.
2. Background in machine learning, data science, or NLP.
3. Experience with recommendation engines or personalization systems.
4. Certification in GCP Professional Machine Learning Engineer or Data Engineer.