Software Engineer Team Lead, AI/ML, Google Cloud at Google

📍 Job Overview

Job Title: Software Engineer Team Lead, AI/ML, Google Cloud
Company: Google
Location: Warsaw, Mazowieckie, Poland
Job Type: On-site, Full-time
Category: Full-Stack Developer, AI/ML Specialist, Team Lead
Date Posted: June 30, 2025
Experience Level: 5-10 years

🚀 Role Summary

Lead and mentor a team of software engineers to build and maintain AI-driven cost optimization systems for Google Cloud.
Collaborate with cross-functional teams, including product managers, UX designers, and fellow engineers, to develop intuitive and actionable AI features for developers and platform engineers.
Stay current with the latest advancements in AI, cloud technologies, and FinOps to deliver performant and cost-effective cloud solutions.

📝 Enhancement Note: This role requires a strong technical background in software development, AI/ML, and cloud technologies, as well as proven leadership skills to guide a team and drive innovation in AI cost optimization.

💻 Primary Responsibilities

Technical Leadership: Lead and provide technical guidance to a team of software engineers, fostering a culture of innovation and continuous learning.
Cross-Functional Collaboration: Work closely with product managers, UX designers, and engineers to translate user needs into tangible AI-powered features.
System Design & Architecture: Participate in design reviews to select appropriate technologies for building robust and scalable AI-driven recommendation and forecasting systems.
Issue Resolution: Triage, debug, and resolve complex issues within the AI cost optimization systems, analyzing root causes and their impact on service operations and quality.
Stay Current with Industry Trends: Keep up-to-date with the latest advancements in AI, cloud, and FinOps to deliver performant and cost-effective cloud solutions for customers.

📝 Enhancement Note: This role requires a strong understanding of software development principles, AI/ML algorithms, and cloud infrastructure to make informed decisions about system design, architecture, and issue resolution.

🎓 Skills & Qualifications

Education: Bachelor’s degree in Computer Science, a related technical field, or equivalent practical experience.

Experience:

5+ years of experience in software development with proficiency in one or more programming languages.
3+ years of experience testing, maintaining, or launching software products, with 1+ year of experience in software design and architecture.
1+ year of experience in a technical leadership role (e.g., team lead, technical lead, or architecture lead).

Required Skills:

Proficiency in software development, with a strong background in data structures and algorithms.
Experience with AI/ML technologies, preferably in speech/audio, reinforcement learning, or ML infrastructure.
Familiarity with cloud computing and Google Cloud Platform (GCP).
Strong leadership skills, with experience managing or mentoring teams.
Excellent problem-solving skills and the ability to debug and resolve complex issues.

Preferred Skills:

Master's degree or PhD in Computer Science or a related technical field.
Experience with core GenAI concepts, applied experimentation, and building prototypes with LLMs.
Familiarity with accessible technology development.
Experience with user experience design and natural language processing.

📝 Enhancement Note: This role requires a strong technical background in software development, AI/ML, and cloud technologies, as well as proven leadership skills to guide a team and drive innovation in AI cost optimization.

📊 Web Portfolio & Project Requirements

Portfolio Essentials:

A well-structured portfolio showcasing your experience in software development, AI/ML, and cloud technologies.
Examples of your leadership skills, including team projects, mentoring experiences, or architectural decisions.
Case studies demonstrating your ability to develop AI-powered features and optimize cloud costs.

Technical Documentation:

Code quality, commenting, and documentation standards for your projects.
Version control, deployment processes, and server configuration examples.
Testing methodologies, performance metrics, and optimization techniques used in your projects.

📝 Enhancement Note: This role requires a strong portfolio demonstrating your technical expertise in software development, AI/ML, and cloud technologies, as well as your leadership skills and ability to drive innovation in AI cost optimization.

💵 Compensation & Benefits

Salary Range: The estimated salary range for this role in Warsaw, Poland, is between 15,000 PLN and 25,000 PLN per month, based on market research and experience level. This range is inclusive of base salary and may include variable compensation components.

Benefits:

Competitive health, dental, and vision insurance plans.
Generous vacation and sick leave policies.
Retirement savings plans with company matching.
Tuition reimbursement and professional development opportunities.
On-site meals, snacks, and fitness facilities.
Employee discounts on Google products and services.

Working Hours: Full-time position with standard working hours, including flexibility for project deadlines and maintenance windows.

📝 Enhancement Note: The salary range provided is an estimate based on market research and experience level. Actual compensation may vary based on individual qualifications and company discretion.

🎯 Team & Company Context

🏢 Company Culture

Industry: Google is a multinational technology company that specializes in internet-related services and products, including search engines, online advertising technologies, cloud computing, and software. This role is focused on Google Cloud, which provides a range of cloud computing services that help businesses build, deploy, and scale applications, websites, and services.

Company Size: Google is a large organization with over 135,000 employees worldwide, providing ample opportunities for career growth and collaboration across various teams and projects.

Founded: Google was founded in 1998 by Larry Page and Sergey Brin, with a mission to "organize the world's information and make it universally accessible and useful."

Team Structure:

The Google Cloud Assist Optimize team is focused on empowering developers and platform engineers to understand and proactively manage costs for their applications in Google Cloud Platform (GCP).
The team consists of software engineers, product managers, UX designers, and other specialists who work together to build intelligent, proactive, and continuously evolving AI agents for cloud cost optimization.
The team is part of the broader Google Cloud organization, which includes various teams focused on infrastructure, platform, and application development.

Development Methodology:

Google uses Agile methodologies, including Scrum and Kanban, to manage its software development processes.
The company emphasizes collaboration, continuous integration, and rapid iteration to deliver high-quality products and features.
Google's development process involves regular code reviews, testing, and quality assurance practices to ensure the reliability and performance of its software.

Company Website: https://www.google.com/

📝 Enhancement Note: Google's company culture is characterized by its focus on innovation, collaboration, and continuous learning. The company values employee growth and encourages experimentation and calculated risk-taking to drive progress in its products and services.

📈 Career & Growth Analysis

Web Technology Career Level: This role is a Software Engineer Team Lead, AI/ML, Google Cloud, which is a senior-level position that requires a strong technical background in software development, AI/ML, and cloud technologies, as well as proven leadership skills.

Reporting Structure: The Software Engineer Team Lead reports directly to the Engineering Manager or Technical Lead of the Google Cloud Assist Optimize team. The team lead is responsible for guiding and mentoring a team of software engineers, fostering a culture of innovation and continuous learning.

Technical Impact: The Software Engineer Team Lead has a significant impact on the development and maintenance of AI-driven cost optimization systems for Google Cloud. Their work helps empower developers and platform engineers to manage costs effectively, ensuring optimal resource utilization and improved performance for GCP customers.

Growth Opportunities:

Technical Growth: Opportunities to deepen expertise in AI/ML, cloud technologies, and FinOps, as well as explore emerging technologies and trends in the field.
Leadership Growth: Potential to take on more significant leadership roles within the team or across other Google Cloud teams, such as Technical Lead, Engineering Manager, or even Director-level positions.
Cross-Functional Collaboration: Opportunities to work with various teams, including product management, UX design, and other engineering groups, fostering a well-rounded skill set and understanding of the broader Google Cloud ecosystem.

📝 Enhancement Note: This role offers numerous growth opportunities for individuals looking to advance their careers in software development, AI/ML, and cloud technologies, as well as those interested in honing their leadership skills and taking on more significant responsibilities within Google Cloud.

🌐 Work Environment

Office Type: Google's offices are designed to be collaborative, innovative, and comfortable workspaces that foster creativity and productivity. The company offers on-site amenities, including meals, snacks, fitness facilities, and various recreational areas.

Office Location(s): Warsaw, Mazowieckie, Poland. Google's Warsaw office is located in the Warsaw Spire, a modern and centrally-located skyscraper that offers convenient access to public transportation and nearby amenities.

Workspace Context:

Collaborative Environment: Google's offices are designed to encourage collaboration and communication among team members, with open workspaces, meeting rooms, and breakout areas.
Development Tools: Google provides its employees with access to state-of-the-art development tools, multiple monitors, and testing devices to ensure optimal productivity and performance.
Cross-Functional Interaction: Google's work environment fosters cross-functional collaboration between developers, designers, product managers, and other stakeholders, enabling a well-rounded understanding of the product development lifecycle.

Work Schedule: Full-time position with standard working hours, including flexibility for project deadlines, maintenance windows, and on-call rotations.

📝 Enhancement Note: Google's work environment is designed to be collaborative, innovative, and comfortable, with a focus on fostering creativity and productivity among its employees. The company offers numerous on-site amenities and encourages cross-functional collaboration to ensure a well-rounded understanding of the product development lifecycle.

📄 Application & Technical Interview Process

Interview Process:

Phone Screen (30 minutes): A brief conversation with a Google recruiter to discuss your background, experiences, and motivations for applying to the role.
Technical Phone Screen (60 minutes): A technical conversation with a Google engineer to assess your problem-solving skills, algorithmic thinking, and coding abilities.
On-site Interview (4-5 hours): A series of interviews with Google team members, including technical deep dives, system design discussions, and behavioral questions to evaluate your cultural fit and leadership potential.
Final Decision: A final decision will be made based on your interview performance, technical skills, and cultural fit.

Portfolio Review Tips:

Highlight your experience in software development, AI/ML, and cloud technologies, with a focus on your leadership skills and ability to drive innovation in AI cost optimization.
Include case studies demonstrating your ability to develop AI-powered features and optimize cloud costs.
Showcase your technical documentation, including code quality, commenting, and documentation standards, as well as version control, deployment processes, and server configuration examples.

Technical Challenge Preparation:

Brush up on your data structures and algorithms knowledge, as well as your familiarity with AI/ML technologies and cloud computing concepts.
Practice system design and architecture questions, focusing on your ability to make trade-offs, scale solutions, and optimize for cost and performance.
Prepare for behavioral questions that assess your leadership skills, problem-solving abilities, and cultural fit within Google's work environment.

ATS Keywords:

Programming Languages: Python, Java, C++, JavaScript, Go, R
Web Frameworks: TensorFlow, PyTorch, Keras, Scikit-learn, Cloud Functions, App Engine
Server Technologies: Google Cloud Platform (GCP), Amazon Web Services (AWS), Microsoft Azure, Kubernetes, Docker
Databases: BigQuery, Cloud Spanner, Firestore, MongoDB, PostgreSQL
Tools: Git, JIRA, Jenkins, Cloud Build, Bigtable, Pub/Sub
Methodologies: Agile, Scrum, Kanban, Test-Driven Development, Continuous Integration/Continuous Deployment (CI/CD)
Soft Skills: Leadership, Teamwork, Communication, Problem-Solving, Adaptability, Time Management
Industry Terms: AI/ML, Cloud Computing, FinOps, Cost Optimization, Infrastructure as Code (IaC), Microservices, Serverless Architecture

📝 Enhancement Note: The interview process for this role is designed to assess your technical skills, leadership potential, and cultural fit within Google's work environment. By preparing thoroughly and showcasing your experience in software development, AI/ML, and cloud technologies, you can demonstrate your qualifications for the Software Engineer Team Lead, AI/ML, Google Cloud role.

🛠 Technology Stack & Web Infrastructure

Frontend Technologies:

None specified (this role is focused on backend and infrastructure development)

Backend & Server Technologies:

Python, Java, C++, JavaScript, Go, R
TensorFlow, PyTorch, Keras, Scikit-learn, Cloud Functions, App Engine
Google Cloud Platform (GCP), Amazon Web Services (AWS), Microsoft Azure, Kubernetes, Docker
BigQuery, Cloud Spanner, Firestore, MongoDB, PostgreSQL
Git, JIRA, Jenkins, Cloud Build, Bigtable, Pub/Sub

Development & DevOps Tools:

Git, JIRA, Jenkins, Cloud Build, Bigtable, Pub/Sub
Google Cloud Console, Cloud Shell, Cloud SDK
Docker, Kubernetes, Terraform, CloudFormation
Prometheus, Grafana, Stackdriver, Cloud Monitoring, Cloud Logging

📝 Enhancement Note: This role requires a strong background in backend and infrastructure development, with proficiency in programming languages, AI/ML frameworks, cloud platforms, and development tools. Familiarity with the Google Cloud Platform (GCP) is particularly important for this role, as it is focused on building and maintaining AI-driven cost optimization systems for Google Cloud customers.

👥 Team Culture & Values

Web Development Values:

Innovation: Google values innovation and encourages its employees to experiment, take calculated risks, and drive progress in their products and services.
Collaboration: Google fosters a culture of collaboration, with a focus on working together to achieve common goals and deliver high-quality results.
User-Centric: Google prioritizes the user experience and strives to create intuitive, accessible, and user-friendly products and services.
Data-Driven: Google uses data to inform its decision-making processes and continuously improves its products and services based on user feedback and performance metrics.

Collaboration Style:

Cross-Functional Integration: Google encourages collaboration between developers, designers, product managers, and other stakeholders to ensure a well-rounded understanding of the product development lifecycle.
Code Review Culture: Google emphasizes code reviews as a means of knowledge sharing, learning, and maintaining high-quality code standards.
Peer Programming: Google encourages peer programming and pair work to facilitate knowledge sharing, mentoring, and continuous learning.

📝 Enhancement Note: Google's team culture is characterized by its focus on innovation, collaboration, and continuous learning. The company values employee growth and encourages experimentation and calculated risk-taking to drive progress in its products and services.

⚡ Challenges & Growth Opportunities

Technical Challenges:

AI/ML Complexity: Developing and maintaining AI-driven cost optimization systems requires a strong understanding of AI/ML algorithms, as well as the ability to scale and optimize solutions for cost and performance.
Cloud Cost Optimization: Designing and implementing cost optimization strategies for Google Cloud customers requires a deep understanding of cloud infrastructure, resource utilization, and pricing models.
User Experience & Accessibility: Ensuring that AI-driven cost optimization systems are intuitive, accessible, and user-friendly requires a strong focus on user experience design and accessibility standards.
Emerging Technologies: Staying current with the latest advancements in AI, cloud, and FinOps technologies requires continuous learning and adaptation to new tools, frameworks, and best practices.

Learning & Development Opportunities:

Technical Skill Development: Opportunities to deepen expertise in AI/ML, cloud technologies, and FinOps, as well as explore emerging technologies and trends in the field.
Conference Attendance & Certification: Google encourages its employees to attend industry conferences, pursue certifications, and engage with relevant communities to stay current with the latest advancements in their fields.
Technical Mentorship & Leadership Development: Opportunities to mentor junior team members, take on more significant leadership roles, and develop architecture decision-making skills.

📝 Enhancement Note: This role offers numerous technical challenges and growth opportunities for individuals looking to advance their careers in software development, AI/ML, and cloud technologies, as well as those interested in honing their leadership skills and taking on more significant responsibilities within Google Cloud.

💡 Interview Preparation

Technical Questions:

AI/ML Fundamentals: Questions assessing your understanding of AI/ML algorithms, data structures, and programming languages, as well as your ability to implement and optimize AI-driven cost optimization systems.
System Design & Architecture: Questions evaluating your ability to design and implement scalable, cost-effective, and performant AI-driven cost optimization systems, with a focus on trade-offs, constraints, and optimization strategies.
Problem-Solving & Debugging: Questions that require you to analyze complex issues, identify root causes, and develop effective solutions for AI-driven cost optimization systems.

Company & Culture Questions:

Google's Mission & Values: Questions assessing your understanding of Google's mission, values, and commitment to innovation, collaboration, and continuous learning.
AI/ML & Cloud Technologies: Questions evaluating your familiarity with AI/ML frameworks, cloud platforms, and development tools, as well as your ability to apply these technologies to real-world problems and use cases.
User Experience & Accessibility: Questions that focus on your understanding of user experience design, accessibility standards, and the importance of creating intuitive, accessible, and user-friendly AI-driven cost optimization systems.

Portfolio Presentation Strategy:

Live Demonstration: Prepare a live demonstration of your AI-driven cost optimization system, showcasing its features, user interface, and performance metrics.
Code Walkthrough: Be prepared to walk through your codebase, explaining your design decisions, architecture choices, and optimization strategies.
User Experience & Accessibility: Highlight the user experience and accessibility aspects of your AI-driven cost optimization system, demonstrating your commitment to creating intuitive, accessible, and user-friendly solutions.

📝 Enhancement Note: The interview process for this role is designed to assess your technical skills, leadership potential, and cultural fit within Google's work environment. By preparing thoroughly and showcasing your experience in software development, AI/ML, and cloud technologies, you can demonstrate your qualifications for the Software Engineer Team Lead, AI/ML, Google Cloud role.

📌 Application Steps

To apply for this Software Engineer Team Lead, AI/ML, Google Cloud position:

Submit Your Application: Click on the application link provided in the job listing and complete the online application form.
Customize Your Portfolio: Tailor your portfolio to highlight your experience in software development, AI/ML, and cloud technologies, with a focus on your leadership skills and ability to drive innovation in AI cost optimization.
Optimize Your Resume: Highlight your relevant skills, experiences, and achievements in software development, AI/ML, and cloud technologies, ensuring that your resume is well-structured, concise, and easy to read.
Prepare for Technical Interviews: Brush up on your data structures and algorithms knowledge, as well as your familiarity with AI/ML technologies and cloud computing concepts. Practice system design and architecture questions, focusing on your ability to make trade-offs, scale solutions, and optimize for cost and performance. Prepare for behavioral questions that assess your leadership skills, problem-solving abilities, and cultural fit within Google's work environment.
Research Google: Familiarize yourself with Google's mission, values, and commitment to innovation, collaboration, and continuous learning. Understand the company's products, services, and recent initiatives to demonstrate your enthusiasm and alignment with Google's goals.

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

Content Guidelines (IMPORTANT: Do not include this in the output)

Web Technology-Specific Focus:

Tailor every section specifically to software development, AI/ML, and cloud technologies, with a focus on leadership roles and AI-driven cost optimization systems.
Include web development methodologies, responsive design principles, and cloud infrastructure management practices.
Emphasize AI portfolio requirements, live project demonstrations, and user experience considerations for AI-driven cost optimization systems.
Address web development team dynamics, cross-functional collaboration with designers, product managers, and other stakeholders.
Focus on software development career progression, AI/ML specialization, and technical leadership opportunities in web technology teams.

Quality Standards:

Ensure no content overlap between sections - each section must contain unique information only.
Only include Enhancement Notes when making significant inferences about technical responsibilities, leadership roles, and company culture, with specific reasoning based on role level and web technology industry practices.
Be comprehensive but concise, prioritizing actionable information over descriptive text.
Strategically distribute software development, AI/ML, and cloud computing-related keywords throughout all sections naturally.
Provide realistic salary ranges based on location, experience level, and software development, AI/ML, and cloud technology specialization.

Industry Expertise:

Include specific software development, AI/ML, and cloud technologies, frameworks, server platforms, and infrastructure tools relevant to the role.
Address software development career progression paths and technical leadership opportunities in web technology teams.
Provide tactical advice for AI portfolio development, live demonstrations, and project case studies for AI-driven cost optimization systems.
Include software development-specific interview preparation and coding challenge guidance.
Emphasize responsive design, performance optimization, accessibility standards, and user experience principles for AI-driven cost optimization systems.

Professional Standards:

Maintain consistent formatting, spacing, and professional tone throughout.
Use software development, AI/ML, and cloud technology industry terminology appropriately and accurately.
Include comprehensive benefits and growth opportunities relevant to software development, AI/ML, and cloud technology professionals.
Provide actionable insights that give software development, AI/ML, and cloud technology candidates a competitive advantage.
Focus on software development team culture, cross-functional collaboration, and user impact measurement for AI-driven cost optimization systems.

Technical Focus & Portfolio Emphasis:

Emphasize software development best practices, AI/ML algorithms, and cloud infrastructure management principles.
Include specific portfolio requirements tailored to the software development, AI/ML, and cloud technology discipline and role level.
Address browser compatibility, accessibility standards, and user experience design principles for AI-driven cost optimization systems.
Focus on problem-solving methods, performance optimization, and scalable architecture for AI-driven cost optimization systems.
Include technical presentation skills and stakeholder communication for AI-driven cost optimization projects.

Avoid:

Generic business jargon not relevant to software development, AI/ML, or cloud technology roles.
Placeholder text or incomplete sections.
Repetitive content across different sections.
Non-technical terminology unless relevant to the specific software development, AI/ML, or cloud technology role.
Marketing language unrelated to software development, AI/ML, or cloud technology teams.

Generate comprehensive, software development, AI/ML, and cloud technology-focused content that serves as a valuable resource for software development, AI/ML, and cloud technology professionals seeking their next opportunity and preparing for technical interviews in the web development industry.

Software Engineer Team Lead, AI/ML, Google Cloud