Vertex AI Architect

We are looking for a GCP Architect with hands-on experience designing and delivering Vertex AI–based solutions. The role focuses on practical architecture, solution design, and guiding engineering teams to build ML, GenAI, and data-driven applications on Google Cloud. You should be strong in GCP fundamentals, comfortable working with AI/ML workflows, and confident in translating business needs into technical architectures that can be delivered reliably. Roles & Responsibilities: ·      Design AI/ML and GenAI solution architectures on GCP using Vertex AI, BigQuery, Cloud Run, Cloud Functions, and GCS. • Set up and configure Vertex AI components (Workbench, Pipelines, Model Registry, Feature Store, Vector Search, Model Deployment). • Work with teams to design ML workflows, including data ingestion, preprocessing, model development, deployment, and monitoring. • Support the build of prompt-based, RAG, and LLM-driven applications using Gemini and Vertex AI Generative AI features. • Collaborate with data engineering teams to integrate models with BigQuery and other GCP data services. • Build MLOps pipelines using Cloud Build, Cloud Deploy, GitHub Actions, and Terraform. • Prepare architecture diagrams, solution documents, and design specifications. • Participate in client workshops to understand use cases and recommend solution approaches. • Review solution designs from engineering teams and ensure alignment with architecture standards. • Support cost estimation, performance optimisation, and deployment planning. • Ensure adherence to security, IAM, network, and governance guidelines on GCP. • Provide technical guidance and mentorship to development and data teams. • Support pre-sales activities when needed (solutioning, estimation, scoping). Requirements: • Strong understanding of Google Cloud Platform architecture: IAM, VPC, networking, compute, logging, monitoring. • Hands-on experience with Vertex AI, including model training, deployment, tuning, and pipelines. • Experience implementing GenAI/LLM-based solutions (Gemini, RAG, embeddings, vector stores). • Knowledge of core machine learning concepts and ability to work with data scientists/ML engineers. • Proficiency with Python, ML frameworks (TensorFlow/PyTorch), and REST APIs. • Practical experience with Terraform, CI/CD, and automation on GCP. • Good understanding of BigQuery, Dataflow/Beam basics, and data modelling. • Ability to produce clean and clear architecture diagrams and documentation. • Strong communication skills and ability to work with clients and internal teams. Good-to-Have Skills • Experience in telecom, Domain • Experience building ML evaluation, monitoring, and drift detection frameworks. • GCP certifications (Professional Cloud Architect / ML Engineer / Data Engineer).