GCP Data & AI Engineer, AS

Core Data Engineering:

• Design, develop, and maintain scalable data pipelines using Python, SQL, and core GCP services.

• Develop and optimize complex SQL queries for data analysis, extraction, and transformation in BigQuery.

• Manage and orchestrate batch data jobs efficiently using Cloud Composer.

• Build and maintain streaming data pipelines using services like Pub/Sub (or Kafka).

• Develop and deploy cloud infrastructure and services using Terraform.

• Automate ETL testing procedures using Python and SQL.

AI & Application Development:

• Design, build, and operationalize AI applications and RAG pipelines on GCP.

• Leverage the Vertex AI platform to train, fine-tune, and deploy machine learning and generative AI models.

• Design and implement agentic workflows to automate complex business processes.

• Develop, consume, and host REST APIs using Python, deploying them as containerized applications on Cloud Run.

• Implement and manage CI/CD pipelines using GitHub Actions to ensure smooth and reliable deployment of data and AI applications.

Operational Excellence & Collaboration:

• Monitor and troubleshoot data and AI pipelines, resolving L3 support issues in a timely manner.

• Collaborate effectively within an agile team using Jira and Confluence.

• Embrace a culture of continuous learning, accepting failures as opportunities to learn and innovate.

• Strategize and implement novel approaches for robust and scalable system design.

Your skills and experience

Mandatory Skills:

• 6-10 years of IT experience as a hands-on technologist.

• Core Languages: Proficient in Python and advanced SQL, with experience in query optimization.

• Cloud Platform: Strong hands-on experience with GCP (Google Cloud Platform). Experience with Azure or AWS is also valuable.

• Core GCP Services: Proven expertise with Big Query, Cloud Composer (or Apache Airflow), and Cloud Run.

• Infrastructure as Code: Proficient in Terraform.

• CI/CD: Experienced in building CI/CD pipelines using GitHub Actions.

Desired Skills & Practical Experience: For the following areas, we are looking for candidates with demonstrable, hands-on experience in applying these technologies to solve practical problems.

• GCP AI/ML Platform: Hands-on experience with the Vertex AI platform (using its Model Garden, training custom models, or deploying endpoints).

• Generative AI: Practical experience building and deploying RAG (Retrieval-Augmented Generation) pipelines. A strong understanding of LLMs (like Gemini) and embedding models is crucial.

• Agentic AI: Familiarity with designing or building agentic workflows and multi-agent systems. Awareness of emerging frameworks like the Google ADK.

• GCP Data Services: Experience with Dataflow, Cloud Functions. Knowledge of Google Kubernetes Engine (GKE) is a plus.

• API Management: Experience with Apigee.

How we’ll support you

• Training and development to help you excel in your career

• Coaching and support from experts in your team

• A culture of continuous learning to aid progression

  • A range of flexible benefits that you can tailor to suit your needs