Vertex AI + ML​/AI Architect

Overview

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, Big Query, 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 Big Query and other GCP data services.
• Build MLOps pipelines using Cloud Build, Cloud Deploy, Git Hub 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).

• 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 (Tensor Flow/PyTorch), and REST APIs.
• Practical experience with Terraform, CI/CD, and automation on GCP.
• Good understanding of Big Query, 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.

• Experience in telecom, domain (e.g., telecommunications).
• Experience building ML evaluation, monitoring, and drift detection frameworks.
• GCP certifications (Professional Cloud Architect / ML Engineer / Data Engineer).

Mid‑Senior level

Full‑time

Design, Art/Creative, and Information Technology

Technology, Information and Internet