Vertex AI + ML/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., * 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).

Do you have experience in Terraform?, * 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).