Senior AI Engineer (Google Cloud Platform

Unleash your biggest strengths, apply skills & knowledge, learn new things, connect with your peers and build your career with us!

#Engineer Of The Future , #Peopleof Many Talents

• h, you’ll encounter friendly people who are eager to explore and reinvent the world of technology.
• We encourage ideas - we like to share and learn from each other. We’re all in for curious & ambitious people.
• Our Technical Management team, possesses a robust technical background. Many of our team members have advanced to strategic roles through internal promotions.
• In a state of mutual willingness to share & grow, our RINFers commit to a minimum tenure of 2.5 years on a project.
• Fail fast, learn fast: we experiment, we iterate, we know when to stop and we don't repeat the same mistakes.
• The right technology stack for the right problem: we don't force technology choices just because we know them; our focus is on solving problems, not on pushing predefined stacks.

We inspire one another to share our tech-works in this amazing and abundant world. So we became developers, innovators, thinkers, software builders, and hardware makers!

Founded in 2006 with 650+ engineers & global presence (8 delivery centers in Europe & North America) we strive to become a leading East-European technology partner for growing organizations in need of digital transformation of their products and services!

• Design, develop, and deploy AI-powered applications and services on Google Cloud Platform.
• Build and maintain scalable microservices-based architectures using modern development patterns, including API-driven, event-driven, and message-driven architectures.
• Develop and integrate solutions leveraging GCP AI services such as Vertex AI, Document AI, Big Query ML, and Agent Development Framework.
• Work with leading Large Language Models (LLMs), including OpenAI, Anthropic Claude, Gemini, and Azure OpenAI.
• Apply advanced prompt engineering, context engineering, and retrieval techniques to maximize AI solution performance.
• Design and implement agentic AI systems using frameworks such as Google Agent Development Kit (ADK).
• Rapidly build Proofs of Concept (POCs) and MVPs using modern AI development and coding assistant tools.
• Develop data processing and analytics workflows using Big Query and related GCP services.
• Build, optimize, and maintain CI/CD pipelines supporting cloud-native AI applications.
• Collaborate with product, business, and engineering teams to identify opportunities where AI can create measurable business value.
• Continuously evaluate emerging AI technologies and recommend innovative solutions.

• Proven hands-on experience developing solutions on Google Cloud Platform.
• Strong experience with GCP AI products and services, including:
  Vertex AI, Document AI, Big Query ML, Agent Development Framework
• Strong knowledge of third-party LLM platforms, such as:
  OpenAI, Anthropic Claude, Google Gemini, Azure OpenAI
• Demonstrated expertise in prompt engineering, context engineering, and LLM orchestration.
• Strong experience with Python development.
• Solid understanding of microservices architecture and distributed systems.
• Experience with API-driven, event-driven, and message-driven development patterns.
• Hands-on experience building agentic AI applications and autonomous workflows.
• Experience with Google Agent Development Kit (ADK) or similar agent frameworks.
• Strong knowledge of Big Query and cloud-based data processing.
• Experience designing and maintaining CI/CD pipelines within Google Cloud environments.
• Familiarity with modern AI coding assistants and rapid prototyping methodologies.
• Excellent problem-solving and communication skills.
• Fluent English, both written and spoken.

• Experience with Retrieval-Augmented Generation (RAG) architectures.
• Experience with vector databases and semantic search solutions.
• Knowledge of Kubernetes, Docker, and cloud-native deployment practices.
• Familiarity with MLOps and AI governance frameworks.
• Experience working in Agile environments.

• Flexible working environment, ability to work remotely or in a hybrid model, depending on your project…