Lead GCP Native Engineering

Be in IT is a recruitment company specializing in comprehensive support for clients in IT technology needs. Operating since 2016 and as a freelancer since 2021, the company focuses on delivering precise and comprehensive job offers and effective recruitment conversations. It holds a certificate from the National Employment Agency Register (number 27663).

• Minimum 10 years of experience in software/cloud engineering, including at least 5 years of practical work with GCP.
• Deep knowledge of native GCP services: GKE, Cloud Run, Cloud Functions, Pub/Sub, BigQuery, Cloud SQL/Spanner, Dataflow, Anthos.
• Solid knowledge of cloud-native architecture: microservices, event-driven design, serverless, containerization.
• Experience with AI/ML on GCP platform: Vertex AI, GenAI, MLOps.
• Documented experience leading engineering teams of several people in client projects.
• Knowledge of DevOps practices: CI/CD, Infrastructure as Code (Terraform), observability, security-by-design.
• Experience in direct client cooperation, including stakeholder management and technical pre-sales.
• Google Cloud Professional certification: Cloud Architect or Cloud Developer.
• English language proficiency at B2 or C1 level enabling fluent communication.

Nice to have:

• Experience with multi-cloud or hybrid-cloud (AWS, Azure, Anthos).
• Background in data engineering or large data platforms.
• Participation in creating RFPs and offer proposals.
• Additional GCP certifications.
• Availability ASAP; acceptable notice period up to one month ending at month-end.

• Long-term collaboration with an international consulting company serving automotive, healthcare, finance, banking, and manufacturing sectors.
• Technical leadership of engineering teams in GCP projects.
• Responsibility for technical direction from design to implementation.
• Acting as the main technical expert in client contacts: stakeholder management, participation in pre-sales.
• Designing and implementing cloud-native solutions: microservices, event-driven, serverless, containerization.
• Working with native GCP services: GKE, Cloud Run, Cloud Functions, Pub/Sub, BigQuery, Cloud SQL/Spanner, Dataflow, Anthos.
• Implementing AI/ML on GCP: Vertex AI, GenAI, MLOps.
• Executing DevOps practices: CI/CD, Infrastructure as Code (Terraform), observability, security-by-design.
• Mentoring and leading teams (several people).
• Translating technical concepts for technical and business audiences.