

Prodapt
GCP Architect
β - Featured Role | Apply direct with Data Freelance Hub
This role is for a GCP Architect in London, on a 1-year fixed-term contract, offering competitive pay. Key skills include GCP architecture, Vertex AI, GenAI solutions, Python, and Terraform. Telecom experience and GCP certifications are preferred.
π - Country
United Kingdom
π± - Currency
Β£ GBP
-
π° - Day rate
Unknown
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ποΈ - Date
November 19, 2025
π - Duration
More than 6 months
-
ποΈ - Location
On-site
-
π - Contract
Inside IR35
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π - Security
Unknown
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π - Location detailed
London Area, United Kingdom
-
π§ - Skills detailed
#REST (Representational State Transfer) #Automation #Terraform #Documentation #VPC (Virtual Private Cloud) #Data Engineering #AI (Artificial Intelligence) #IAM (Identity and Access Management) #Cloud #REST API #Model Deployment #Monitoring #ML (Machine Learning) #TensorFlow #Dataflow #BigQuery #Deployment #Data Ingestion #Data Science #PyTorch #GCP (Google Cloud Platform) #Logging #Security #Python #GitHub
Role 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. Prodaptβs 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 AIβbased 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
β’ Design AI/ML and GenAI solution architectures on GCP using Vertex AI, BigQuery, Cloud Run, Cloud Functions, and GCS.
β’ Set up and configure Vertex AI components (Workbench, Pipelines, Model Registry, Feature Store, Vector Search, Model Deployment).
β’ Work with teams to design ML workflows, including data ingestion, preprocessing, model development, deployment, and monitoring.
β’ Support the build of prompt-based, RAG, and LLM-driven applications using Gemini and Vertex AI Generative AI features.
β’ Collaborate with data engineering teams to integrate models with BigQuery and other GCP data services.
β’ Build MLOps pipelines using Cloud Build, Cloud Deploy, GitHub Actions, and Terraform.
β’ Prepare architecture diagrams, solution documents, and design specifications.
β’ Participate in client workshops to understand use cases and recommend solution approaches.
β’ Review solution designs from engineering teams and ensure alignment with architecture standards.
β’ Support cost estimation, performance optimisation, and deployment planning.
β’ Ensure adherence to security, IAM, network, and governance guidelines on GCP.
β’ Provide technical guidance and mentorship to development and data teams.
β’ Support pre-sales activities when needed (solutioning, estimation, scoping).
Required Skills
β’ Strong understanding of Google Cloud Platform architecture: IAM, VPC, networking, compute, logging, monitoring.
β’ Hands-on experience with Vertex AI, including model training, deployment, tuning, and pipelines.
β’ Experience implementing GenAI/LLM-based solutions (Gemini, RAG, embeddings, vector stores).
β’ Knowledge of core machine learning concepts and ability to work with data scientists/ML engineers.
β’ Proficiency with Python, ML frameworks (TensorFlow/PyTorch), and REST APIs.
β’ Practical experience with Terraform, CI/CD, and automation on GCP.
β’ Good understanding of BigQuery, Dataflow/Beam basics, and data modelling.
β’ Ability to produce clean and clear architecture diagrams and documentation.
β’ Strong communication skills and ability to work with clients and internal teams.
Good-to-Have Skills
β’ Experience in telecom, Domain
β’ Experience building ML evaluation, monitoring, and drift detection frameworks.
β’ GCP certifications (Professional Cloud Architect / ML Engineer / Data Engineer).
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. Prodaptβs 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 AIβbased 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
β’ Design AI/ML and GenAI solution architectures on GCP using Vertex AI, BigQuery, Cloud Run, Cloud Functions, and GCS.
β’ Set up and configure Vertex AI components (Workbench, Pipelines, Model Registry, Feature Store, Vector Search, Model Deployment).
β’ Work with teams to design ML workflows, including data ingestion, preprocessing, model development, deployment, and monitoring.
β’ Support the build of prompt-based, RAG, and LLM-driven applications using Gemini and Vertex AI Generative AI features.
β’ Collaborate with data engineering teams to integrate models with BigQuery and other GCP data services.
β’ Build MLOps pipelines using Cloud Build, Cloud Deploy, GitHub Actions, and Terraform.
β’ Prepare architecture diagrams, solution documents, and design specifications.
β’ Participate in client workshops to understand use cases and recommend solution approaches.
β’ Review solution designs from engineering teams and ensure alignment with architecture standards.
β’ Support cost estimation, performance optimisation, and deployment planning.
β’ Ensure adherence to security, IAM, network, and governance guidelines on GCP.
β’ Provide technical guidance and mentorship to development and data teams.
β’ Support pre-sales activities when needed (solutioning, estimation, scoping).
Required Skills
β’ Strong understanding of Google Cloud Platform architecture: IAM, VPC, networking, compute, logging, monitoring.
β’ Hands-on experience with Vertex AI, including model training, deployment, tuning, and pipelines.
β’ Experience implementing GenAI/LLM-based solutions (Gemini, RAG, embeddings, vector stores).
β’ Knowledge of core machine learning concepts and ability to work with data scientists/ML engineers.
β’ Proficiency with Python, ML frameworks (TensorFlow/PyTorch), and REST APIs.
β’ Practical experience with Terraform, CI/CD, and automation on GCP.
β’ Good understanding of BigQuery, Dataflow/Beam basics, and data modelling.
β’ Ability to produce clean and clear architecture diagrams and documentation.
β’ Strong communication skills and ability to work with clients and internal teams.
Good-to-Have Skills
β’ Experience in telecom, Domain
β’ Experience building ML evaluation, monitoring, and drift detection frameworks.
β’ GCP certifications (Professional Cloud Architect / ML Engineer / Data Engineer).






