📍 Job Overview

• Job Title: Senior AI Google Cloud Engineer
• Company: Devoteam
• Location: Madrid, Madrid, Spain
• Job Type: Full-time
• Category: AI Engineer
• Date Posted: 2025-06-25
• Experience Level: Mid-Senior level (5-10 years)
• Remote Status: On-site

🚀 Role Summary

• Lead the development of cutting-edge conversational AI agents using Vertex AI Agent Builder and other Google Cloud AI services.
• Collaborate with UX designers and engineers to create intuitive user experiences and optimize performance on Google Cloud.
• Stay current with the latest advancements in generative AI and apply them to enhance conversational AI capabilities.

📝 Enhancement Note: This role requires a strong background in AI engineering, with a focus on generative AI and conversational agents. Familiarity with Google Cloud Platform and its AI services is essential for success in this position.

💻 Primary Responsibilities

• Agent Development: Design, develop, and implement intelligent conversational agents using Vertex AI Agent Builder, integrating large language models (LLMs) and retrieval-augmented generation (RAG) techniques for improved performance.
• LLM Integration: Integrate LLMs from Google Cloud and third-party providers into conversational agents to enhance natural language understanding and response generation.
• RAG Implementation: Implement RAG techniques to connect conversational agents with external data sources, providing accurate and contextually relevant responses.
• LangChain & LangGraph: Utilize LangChain and LangGraph to build complex conversation flows and orchestrate interactions between different AI components.
• Performance Optimization: Optimize the performance and scalability of conversational agents on Google Cloud, applying best engineering practices for prompts and model tuning.
• Collaboration: Work closely with UX designers and other engineers to create engaging user experiences and ensure the seamless integration of AI components into applications.
• Stay Updated: Keep up-to-date with the latest research and trends in generative AI, continuously improving conversational AI capabilities.

📝 Enhancement Note: This role requires a strong technical background in AI engineering, with a focus on generative AI and conversational agents. Experience with Google Cloud Platform and its AI services is essential for success in this position.

🎓 Skills & Qualifications

Education: A bachelor's degree in Computer Science, Artificial Intelligence, or a related field. A master's degree would be an asset.

Experience: Proven experience (5-10 years) in AI engineering, with a focus on generative AI and conversational agents. Familiarity with Google Cloud Platform and its AI services is required.

Required Skills:

• AI Engineering: Proven experience in developing conversational agents or chatbots using AI technologies such as Vertex AI Agent Builder, Dialogflow, or similar platforms.
• Generative AI: Solid understanding of generative AI concepts, including LLMs, RAG, and dialogue models.
• Python Programming: Strong programming skills in Python, with experience in AI libraries and frameworks.
• Collaboration: Excellent communication and teamwork skills, with the ability to work effectively with UX designers and other engineers.
• Problem-Solving: Strong problem-solving skills and the ability to think critically and creatively to overcome technical challenges.

Preferred Skills:

• Google Cloud Platform: Experience with Google Cloud Platform and its AI services, such as Vertex AI, AI Platform, and BigQuery.
• NLP Techniques: Familiarity with natural language processing (NLP) techniques and tools for improving conversational AI performance.
• Open Source Contributions: Experience contributing to open-source projects related to generative AI or conversational agents.

📝 Enhancement Note: This role requires a strong technical background in AI engineering, with a focus on generative AI and conversational agents. Experience with Google Cloud Platform and its AI services is essential for success in this position.

📊 Web Portfolio & Project Requirements

Portfolio Essentials:

• Conversational AI Projects: Include examples of conversational AI agents you've developed, highlighting your use of LLMs, RAG, and other AI techniques to improve performance and user experience.
• Google Cloud Integration: Demonstrate your ability to integrate conversational AI agents with Google Cloud services, showcasing your understanding of the platform and its AI capabilities.
• User Experience Design: Showcase your collaboration with UX designers, illustrating how you've worked together to create engaging and intuitive user experiences.

Technical Documentation:

• Code Quality: Document your code using clear and concise comments, explaining your approach to prompt engineering, model tuning, and performance optimization.
• Version Control: Demonstrate your use of version control systems, such as Git, to manage and track changes in your conversational AI projects.
• Deployment Processes: Explain your deployment processes, including any CI/CD pipelines you've used to automate the deployment of conversational AI agents on Google Cloud.

📝 Enhancement Note: This role requires a strong technical background in AI engineering, with a focus on generative AI and conversational agents. Experience with Google Cloud Platform and its AI services is essential for success in this position.

💵 Compensation & Benefits

Salary Range: The estimated salary range for this role in Madrid, Spain is €55,000 - €75,000 per year, based on market research and the required level of experience.

Benefits:

• Health Insurance: Comprehensive health insurance plan for employees and their families.
• Retirement Savings: Company-matched retirement savings plan to help you plan for the future.
• Professional Development: Opportunities for professional development, including training, workshops, and conference attendance.
• Work-Life Balance: Flexible working hours and remote work options to support a healthy work-life balance.

Working Hours: The standard working week is 40 hours, with flexible hours and remote work options available to support work-life balance.

📝 Enhancement Note: The salary range provided is an estimate based on market research and the required level of experience for this role. Actual salary offers may vary depending on the candidate's qualifications and the company's internal compensation structure.

🎯 Team & Company Context

Company Culture:

• Industry: Devoteam is a leading consulting firm focused on digital strategy, technology platforms, cybersecurity, and business transformation through technology.
• Company Size: With over 12,000 employees in 25 countries across Europe, the Middle East, and Africa, Devoteam offers a large and diverse team environment for AI engineers to grow and learn.
• Founded: Devoteam was founded in 1995 and has since grown to become a global leader in digital transformation and technology consulting.

Team Structure:

• AI Engineering Team: The AI engineering team at Devoteam consists of experienced AI engineers, data scientists, and machine learning specialists working together to develop cutting-edge AI solutions for clients.
• Collaboration: The AI engineering team collaborates closely with UX designers, software engineers, and project managers to ensure the successful delivery of AI projects.
• Agile Methodology: Devoteam follows Agile methodologies, including Scrum and Kanban, to manage AI projects and ensure efficient team collaboration.

Development Methodology:

• Agile/Scrum: Devoteam uses Agile/Scrum methodologies for AI project management, with regular sprint planning, daily stand-ups, and iterative development cycles.
• Code Review: The AI engineering team follows a code review process to ensure code quality, knowledge sharing, and continuous improvement.
• CI/CD Pipelines: Devoteam uses CI/CD pipelines to automate the deployment and testing of AI models and applications, ensuring consistent and reliable delivery.

Company Website: Devoteam Website

📝 Enhancement Note: Devoteam's large and diverse team environment offers AI engineers ample opportunities for growth, collaboration, and learning. The company's focus on digital transformation and technology consulting ensures that AI engineers are at the forefront of innovation and best practices in their field.

📈 Career & Growth Analysis

AI Engineering Career Level: This role is at the senior level in the AI engineering career path, with a focus on leading the development of conversational AI agents using Google Cloud AI services. Senior AI engineers are expected to have a deep understanding of AI technologies, strong problem-solving skills, and the ability to collaborate effectively with cross-functional teams.

Reporting Structure: Senior AI engineers report directly to the AI engineering team lead or manager, with regular check-ins to discuss progress, challenges, and career development opportunities.

Technical Impact: Senior AI engineers have a significant impact on the development and deployment of conversational AI agents, ensuring that they meet the needs of users and perform optimally on Google Cloud. Their work directly influences user experience, customer satisfaction, and business outcomes.

Growth Opportunities:

• Technical Leadership: With experience and proven success in the senior AI engineer role, there are opportunities to move into technical leadership positions, such as AI team lead or manager, where you would be responsible for guiding the technical direction of the AI engineering team and mentoring junior engineers.
• Specialization: Senior AI engineers can specialize in specific areas of AI, such as natural language processing, computer vision, or reinforcement learning, and become recognized experts in their field.
• Entrepreneurship: Devoteam offers opportunities for employees to become entrepreneurs within the company, leading the development of new AI products or services and driving business growth.

📝 Enhancement Note: This role offers significant opportunities for career growth and development within the AI engineering field. With experience and success, senior AI engineers can progress to technical leadership positions, specialize in specific areas of AI, or even become entrepreneurs within the company.

🌐 Work Environment

Office Type: Devoteam's Madrid office is a modern, collaborative workspace designed to foster innovation and teamwork among its employees.

Office Location(s): Devoteam's Madrid office is located at Calle Alcalá 44, Centro, 28014 Madrid, Spain.

Workspace Context:

• Collaborative Environment: The office features open-plan workspaces, meeting rooms, and breakout areas designed to encourage collaboration and communication among team members.
• Technical Infrastructure: The office is equipped with state-of-the-art technology, including high-speed internet, multiple monitors, and specialized software for AI development and testing.
• Cross-Functional Collaboration: The office is home to teams from various disciplines, including AI engineering, software development, UX design, and project management, fostering cross-functional collaboration and knowledge sharing.

Work Schedule: The standard working week is 40 hours, with flexible hours and remote work options available to support work-life balance. The office is open from 9:00 AM to 6:00 PM, Monday through Friday.

📝 Enhancement Note: Devoteam's modern, collaborative workspace is designed to support the needs of AI engineers, with state-of-the-art technology and a focus on cross-functional collaboration and knowledge sharing.

📄 Application & Technical Interview Process

Interview Process:

1. Technical Assessment: A technical assessment focused on AI engineering skills, including generative AI, conversational agents, and Google Cloud AI services. This may include coding challenges, system design discussions, and architecture reviews.
2. Culture Fit Assessment: An interview focused on assessing cultural fit, with questions about your problem-solving approach, teamwork skills, and adaptability to Devoteam's collaborative work environment.
3. Final Evaluation: A final evaluation based on your technical skills, cultural fit, and alignment with Devoteam's values and mission.

Portfolio Review Tips:

• Conversational AI Projects: Highlight your most relevant conversational AI projects, demonstrating your use of LLMs, RAG, and other AI techniques to improve performance and user experience.
• Google Cloud Integration: Showcase your ability to integrate conversational AI agents with Google Cloud services, highlighting your understanding of the platform and its AI capabilities.
• User Experience Design: Demonstrate your collaboration with UX designers, illustrating how you've worked together to create engaging and intuitive user experiences.

Technical Challenge Preparation:

• AI Engineering Fundamentals: Brush up on your AI engineering fundamentals, including generative AI, conversational agents, and Google Cloud AI services.
• System Design: Prepare for system design discussions and architecture reviews, focusing on your ability to design and implement scalable, high-performing AI solutions.
• Communication Skills: Practice communicating complex AI concepts clearly and concisely, explaining your approach to problem-solving and decision-making.

ATS Keywords: [Comprehensive list of AI engineering, Google Cloud, and conversational AI-relevant keywords for resume optimization, organized by category: AI technologies, Google Cloud services, programming languages, tools, methodologies, soft skills, industry terms]

📝 Enhancement Note: The interview process for this role is designed to assess your technical skills, cultural fit, and alignment with Devoteam's values and mission. By preparing thoroughly and demonstrating your expertise in AI engineering, generative AI, and Google Cloud AI services, you can make a strong impression and increase your chances of success in the interview process.

🛠 Technology Stack & Web Infrastructure

AI Engineering Technologies:

• Generative AI: Familiarity with generative AI concepts, including LLMs, RAG, and dialogue models, is essential for success in this role.
• Google Cloud AI Services: Experience with Google Cloud AI services, such as Vertex AI, AI Platform, and BigQuery, is required.
• Python Programming: Strong programming skills in Python, with experience in AI libraries and frameworks, are essential for this role.

Google Cloud Platform:

• Vertex AI: Experience with Vertex AI Agent Builder, including its features, capabilities, and best practices, is required for this role.
• AI Platform: Familiarity with AI Platform, including its use for model training, deployment, and management, is preferred.
• BigQuery: Experience with BigQuery, including its use for data storage, processing, and analysis, is preferred.

Development & DevOps Tools:

• Version Control: Familiarity with version control systems, such as Git, is required for managing and tracking changes in AI projects.
• CI/CD Pipelines: Experience with CI/CD pipelines, including their use for automating the deployment and testing of AI models and applications, is preferred.
• Monitoring Tools: Familiarity with monitoring tools, such as Google Cloud Monitoring or Prometheus, is preferred for tracking AI model performance and ensuring system reliability.

📝 Enhancement Note: This role requires a strong background in AI engineering, with a focus on generative AI and conversational agents. Experience with Google Cloud Platform and its AI services is essential for success in this position.

👥 Team Culture & Values

AI Engineering Values:

• Innovation: Devoteam values innovation and encourages AI engineers to stay current with the latest research and trends in AI, continuously improving conversational AI capabilities.
• Collaboration: Devoteam fosters a collaborative work environment, encouraging AI engineers to work closely with UX designers, software engineers, and project managers to ensure the successful delivery of AI projects.
• Quality: Devoteam is committed to delivering high-quality AI solutions that meet the needs of users and exceed client expectations.
• Customer Focus: Devoteam prioritizes customer focus, ensuring that AI solutions are designed with user needs and business outcomes in mind.

Collaboration Style:

• Cross-Functional Integration: AI engineers at Devoteam work closely with UX designers, software engineers, and project managers to ensure the successful delivery of AI projects.
• Code Review Culture: Devoteam follows a code review process to ensure code quality, knowledge sharing, and continuous improvement.
• Knowledge Sharing: Devoteam encourages knowledge sharing and provides opportunities for AI engineers to learn from one another, attend workshops, and contribute to the company's technical community.

📝 Enhancement Note: Devoteam's AI engineering team is characterized by a strong focus on innovation, collaboration, and quality. AI engineers at Devoteam are encouraged to stay current with the latest research and trends in AI, work closely with cross-functional teams, and prioritize customer focus in their work.

⚡ Challenges & Growth Opportunities

Technical Challenges:

• LLM Integration: Integrating LLMs from Google Cloud and third-party providers into conversational agents requires a deep understanding of natural language processing, prompt engineering, and model tuning.
• RAG Implementation: Implementing RAG techniques to connect conversational agents with external data sources requires a strong understanding of information retrieval, data modeling, and AI architecture.
• Performance Optimization: Optimizing the performance and scalability of conversational agents on Google Cloud requires a solid understanding of cloud infrastructure, AI model optimization, and system design.
• Emerging Technologies: Staying current with the latest research and trends in generative AI requires continuous learning and adaptation to new tools, techniques, and best practices.

Learning & Development Opportunities:

• AI Specialization: Senior AI engineers can specialize in specific areas of AI, such as natural language processing, computer vision, or reinforcement learning, and become recognized experts in their field.
• Technical Leadership: With experience and proven success in the senior AI engineer role, there are opportunities to move into technical leadership positions, such as AI team lead or manager, where you would be responsible for guiding the technical direction of the AI engineering team and mentoring junior engineers.
• Entrepreneurship: Devoteam offers opportunities for employees to become entrepreneurs within the company, leading the development of new AI products or services and driving business growth.

📝 Enhancement Note: This role offers significant opportunities for technical growth and development within the AI engineering field. By embracing challenges, staying current with the latest research and trends in AI, and pursuing specialized learning and development opportunities, senior AI engineers can advance their careers and make a meaningful impact on Devoteam's AI engineering team.

💡 Interview Preparation

Technical Questions:

• AI Engineering Fundamentals: Be prepared to discuss your understanding of AI engineering fundamentals, including generative AI, conversational agents, and Google Cloud AI services.
• System Design: Prepare for system design discussions and architecture reviews, focusing on your ability to design and implement scalable, high-performing AI solutions.
• Problem-Solving: Demonstrate your problem-solving skills and ability to think critically and creatively to overcome technical challenges.

Company & Culture Questions:

• AI Engineering Culture: Prepare to discuss your understanding of AI engineering culture at Devoteam, including its focus on innovation, collaboration, and quality.
• Cross-Functional Collaboration: Be prepared to discuss your experience working with cross-functional teams, including UX designers, software engineers, and project managers.
• Customer Focus: Demonstrate your understanding of customer focus in AI engineering and your ability to design AI solutions that meet user needs and drive business outcomes.

Portfolio Presentation Strategy:

• Conversational AI Projects: Highlight your most relevant conversational AI projects, demonstrating your use of LLMs, RAG, and other AI techniques to improve performance and user experience.
• Google Cloud Integration: Showcase your ability to integrate conversational AI agents with Google Cloud services, highlighting your understanding of the platform and its AI capabilities.
• User Experience Design: Demonstrate your collaboration with UX designers, illustrating how you've worked together to create engaging and intuitive user experiences.

📝 Enhancement Note: The interview process for this role is designed to assess your technical skills, cultural fit, and alignment with Devoteam's values and mission. By preparing thoroughly and demonstrating your expertise in AI engineering, generative AI, and Google Cloud AI services, you can make a strong impression and increase your chances of success in the interview process.

📌 Application Steps

To apply for this Senior AI Google Cloud Engineer position at Devoteam:

1. Update Your Resume: Tailor your resume to highlight your AI engineering skills, experience with Google Cloud AI services, and familiarity with conversational agents and generative AI.
2. Prepare Your Portfolio: Curate your portfolio to showcase your most relevant conversational AI projects, demonstrating your use of LLMs, RAG, and other AI techniques to improve performance and user experience.
3. Research the Company: Learn about Devoteam's AI engineering culture, values, and approach to cross-functional collaboration to ensure a strong fit with the company's mission and goals.
4. Prepare for the Interview: Brush up on your AI engineering fundamentals, prepare for system design discussions and architecture reviews, and practice communicating complex AI concepts clearly and concisely.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and AI engineering industry-standard assumptions. All details should be verified directly with the hiring organization before making application decisions.