Staff Forward Deployed Engineer, GenAI, Google Cloud

Staff Forward Deployed Engineer, GenAI, Google Cloud

Full-Time 80000 - 100000 £ / year (est.) No working from home possible
Google

At a Glance

  • Tasks: Lead the development of AI applications and bridge the gap between cutting-edge tech and real-world solutions.
  • Company: Join Google Cloud, a leader in AI innovation and technology.
  • Benefits: Competitive salary, inclusive culture, and access to advanced AI tools.
  • Other info: Collaborative environment with opportunities for mentorship and career growth.
  • Why this job: Be at the forefront of the AI revolution and make a tangible impact on businesses worldwide.
  • Qualifications: 8 years of experience in AI solutions and strong coding skills in Python or Typescript.

The predicted salary is between 80000 - 100000 £ per year.

Minimum Qualifications

  • Bachelor’s degree in Engineering, Computer Science, a related field, or equivalent practical experience.
  • 8 years of experience building and shipping production-grade AI-driven solutions to external or internal customers using Python, Typescript or comparable languages.
  • Experience leading technical discovery sessions with business stakeholders and engineering teams to define AI and hardware infrastructure requirements.
  • Experience designing and building AI systems on cloud platforms (e.g., Google Cloud Platform (GCP)).
  • Experience building pipelines for structured, unstructured data, incorporating vector databases and Retrieval-Augmented Generation (RAG)-like architectures to power enterprise-grade AI solutions.

Preferred Qualifications

  • Master’s degree or PhD in AI, Computer Science, or a related technical field.
  • Experience implementing multi-agent systems using frameworks (e.g., LangGraph, CrewAI, or Google’s Agent Development Kit (ADK)) and patterns like ReAct, self-reflection, and hierarchical delegation.
  • Knowledge of large language model native metrics (tokens/sec, cost-per-request) and techniques for optimizing state management and granular tracing.

About The Job

As a GenAI Forward Deployed Engineer at Google Cloud, you will be an embedded builder bridging the gap between frontier AI products and production-grade reality for our customers. You will function as a builder-consultant, moving beyond high-level architecture to code, debug, and jointly ship bespoke agentic solutions directly within the customer’s environment. In this role, you will manage blockers to production including solving the integration complexities, data readiness issues, and state-management issues that prevent AI from reaching enterprise-grade maturity. By embedding with accounts, you will serve a dual purpose: providing white-glove deployment of AI systems and acting as a critical feedback loop, transforming real-world field insights into Google Cloud’s future product roadmap.

It's an exciting time to join Google Cloud’s Go-To-Market team, leading the AI revolution for businesses worldwide. You’ll excel by leveraging Google’s brand credibility—an legacy built on inventing foundational technologies and proven at scale. We’ll provide you with the world’s most advanced AI portfolio, including frontier Gemini models, and the complete Vertex AI platform, helping you to solve business problems. We’re a collaborative culture providing direct access to DeepMind’s engineering and research minds, empowering you to solve customer challenges. Join us to be the catalyst for our mission, drive customer success, and define the new cloud era—the market is yours.

Responsibilities

  • Serve as the lead developer for AI applications, transitioning from rapid prototypes to production-grade agentic workflows (e.g., multi-agent systems, model context protocol servers) that drive measurable return on investment.
  • Architect and code the connective tissue between Google’s AI products and customer's live infrastructure, including APIs, legacy data silos, and security perimeters.
  • Build high-performance evaluation pipelines and observability frameworks to ensure agentic systems meet rigorous requirements for accuracy, safety, and latency.
  • Identify repeatable field patterns and technical friction points in Google’s AI stack, converting them into reusable modules or product feature requests for engineering teams.
  • Drive engineering excellence by mentoring talent, co-building with customer teams, and influencing cross-functional strategies to uplevel organizational technical capabilities.

Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements.

If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

Staff Forward Deployed Engineer, GenAI, Google Cloud employer: Google

At Google Cloud, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration. As a Staff Forward Deployed Engineer, you'll have access to cutting-edge AI technologies and the opportunity to work closely with industry leaders, driving meaningful impact for our customers. We are committed to your professional growth, providing mentorship and resources to help you excel in your career while contributing to the forefront of the AI revolution.

Google

Contact Details:

Google Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Staff Forward Deployed Engineer, GenAI, Google Cloud

Tip Number 1

Network like a pro! Reach out to folks in your industry, especially those at Google Cloud. A friendly chat can open doors that a CV just can't.

Tip Number 2

Show off your skills! Create a portfolio showcasing your AI-driven projects. This is your chance to demonstrate your expertise in Python, Typescript, and cloud platforms.

Tip Number 3

Prepare for technical interviews by brushing up on your knowledge of AI systems and cloud architecture. Practice explaining complex concepts in simple terms—this will impress the interviewers!

Tip Number 4

Don't forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about their job search.

We think you need these skills to ace Staff Forward Deployed Engineer, GenAI, Google Cloud

Python
Typescript
AI-driven solutions
Cloud Platforms (e.g., Google Cloud Platform)
Data Pipelines
Vector Databases
Retrieval-Augmented Generation (RAG)

Some tips for your application 🫡

Show Off Your Skills:Make sure to highlight your experience with AI-driven solutions and the languages you’ve used, like Python or Typescript. We want to see how you've built and shipped production-grade systems, so don’t hold back on the details!

Tailor Your Application:Take a moment to customise your application for this role. Mention specific projects where you’ve led technical discovery sessions or designed AI systems on cloud platforms. This helps us see how you fit into our team!

Be Clear and Concise:When writing your application, keep it straightforward. Use clear language to describe your experiences and avoid jargon unless it’s relevant. We appreciate clarity as much as complexity!

Apply Through Our Website:Don’t forget to submit your application through our website! It’s the best way for us to receive your info and ensures you’re considered for the role. We can’t wait to hear from you!

How to prepare for a job interview at Google

Know Your Tech Inside Out

Make sure you’re well-versed in Python, Typescript, and any other relevant languages. Brush up on your experience with AI-driven solutions and be ready to discuss specific projects where you’ve built production-grade systems.

Prepare for Technical Discovery Sessions

Since you'll be leading technical discussions, practice articulating how you define AI and hardware infrastructure requirements. Think of examples where you've successfully collaborated with stakeholders and engineering teams to solve complex problems.

Familiarise Yourself with Google Cloud Tools

Get comfortable with Google Cloud Platform and its AI offerings. Understand how to build pipelines for both structured and unstructured data, and be prepared to discuss your experience with vector databases and RAG architectures.

Showcase Your Problem-Solving Skills

Be ready to share instances where you’ve tackled integration complexities or data readiness issues. Highlight your ability to transform field insights into actionable feedback, demonstrating your role as a builder-consultant.