Total Vacancy:

1

Job Location:

London, United Kingdom

Working Mode:

Hybrid

Salary Range:

£80,000 - £90,000 per year

Qualification:

Graduate

Experience:

8 to 10 years

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.

Preferred Skills:

•            Experience in telecom, Domain

•            Experience building ML evaluation, monitoring, and drift detection frameworks.

•            GCP certifications (Professional Cloud Architect / ML Engineer / Data Engineer).