GCP Architect

Prodapt; City Of London; On-site; GBP 70,000 - 90,000; Full time

Job summary

A leading technology firm in London is seeking a GCP Architect to design and deliver AI/ML solutions using Google Cloud technologies. The role involves building architecture, mentoring teams, and collaborating with clients to meet business needs. Candidates should have strong knowledge of Google Cloud Platform, particularly in Vertex AI, along with a solid understanding of machine learning workflows. This is a fixed-term position with an emphasis on innovative cloud solutions.

Qualifications

• Strong understanding of Google Cloud architecture: IAM, VPC, networking.
• Experience with Vertex AI including model training and deployment.
• Knowledge of ML concepts and ability to work with data scientists.

Responsibilities

• Design AI/ML solution architectures on GCP using Vertex AI.
• Collaborate with teams to design ML workflows.
• Support pre-sales activities when needed.

Skills

Google Cloud Platform architecture

Vertex AI

GenAI/LLM-based solutions

Machine learning concepts

Python

Terraform

BigQuery

Strong communication skills

Tools

TensorFlow

PyTorch

Cloud Build

Cloud Deploy

GitHub Actions

Job description

Role: GCP Architect

Location & Travel: London

Employment Type : 1 Year Fixed term

Candidate Should be able to start as soon as possible

About Company:

Prodapt is the largest & fastest growing specialized firm serving in Connectedness vertical.

Present across 5 continents, delivering futuristic solutions & AI-driven services to global CSPs, and digital platform & software firms. Prodapt’s customers range from telecom operators, digital/multi-service providers (D/MSPs), technology and digital platform companies in the business of connectedness. Prodapt builds, integrates, and operates solutions enabling next-generation technologies and innovations.

Role 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.

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).

Required Skills

• 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).