Forward Deployed Engineer, Google Cloud Consulting

Forward Deployed Engineer, Google Cloud Consulting Overview

This role sits within Google Cloud Consulting and is focused on bringing advanced AI systems into real customer environments. Rather than acting as a purely advisory consultant, the engineer is expected to work as a hands-on builder who can code, troubleshoot, and help deliver bespoke agentic solutions alongside customers. The position is aimed at engineers who are comfortable taking ownership, moving quickly, and working with a founder-like mindset to remove the technical barriers that keep AI systems from reaching production quality.

The work centers on helping customers move from experimentation to real deployment. That includes solving integration challenges, addressing data readiness problems, and handling state-management issues that often prevent AI applications from operating reliably at enterprise scale. By working directly with accounts, the engineer also helps create a feedback loop between customer needs and Google Cloud’s product direction, turning field experience into insights that can influence future platform improvements.

This is part of Google Cloud’s go-to-market effort, with a strong emphasis on helping businesses adopt AI successfully. The role gives access to Google’s broader AI portfolio, including Gemini models and the Vertex AI platform, and offers the chance to collaborate with DeepMind expertise while solving practical customer problems. The posting presents the opportunity as a chance to help shape the next phase of cloud adoption and AI-driven transformation for customers.

What you will do

• Build complex AI applications and take them from early prototypes into production-ready agentic workflows, including multi-agent systems and MCP server-based solutions that deliver clear business impact.
• Develop the integration layer between Google’s AI products and the customer’s live systems, connecting APIs, older data stores, and security controls as part of a specialist delivery team.
• Create robust evaluation pipelines and observability tooling so agentic systems can be measured for accuracy, safety, and latency.
• Identify recurring patterns and pain points seen in customer engagements, then turn those findings into reusable modules or formal feature requests for Google’s engineering teams.
• Work jointly with pre-sales and product partners to promote strong engineering practices and support long-term adoption and success of delivered solutions.

What you need

• A bachelor’s degree in engineering, computer science, a related field, or equivalent practical experience.
• At least five years of software development experience using Python or a similar language.
• Demonstrated success bringing AI-driven products from concept through launch in production settings.
• Experience designing AI architectures on cloud platforms such as Google Cloud Platform.
• Experience creating pipelines for both structured and unstructured data, using vector databases and retrieval-augmented generation-style approaches to support enterprise AI use cases.
• Experience running technical discovery sessions with customers.
• A master’s degree or PhD in AI, computer science, or another closely related technical discipline is preferred.
• Experience building multi-agent systems using tools such as LangGraph, CrewAI, or ADK, along with advanced design patterns such as ReAct, self-reflection, and hierarchical delegation.
• Experience in post-sales delivery or technical consulting is preferred.
• Knowledge of LLM-oriented operational metrics such as tokens per second and cost per request, plus methods for improving state handling and adding fine-grained tracing.
• The role is described as mid-level, meaning the successful candidate should be able to drive progress, solve problems independently, and mentor more junior team members.
• English proficiency is required for all roles unless the posting explicitly says otherwise.

Additional context

The position is based in London, UK, and the posting does not describe a remote or hybrid arrangement. It is presented as a customer-facing engineering role within Google Cloud Consulting, with a strong emphasis on practical delivery, collaboration, and technical depth.

Google states that it is an equal opportunity and affirmative action employer and says it is committed to building a workforce that reflects the people it serves. The company notes that it considers applicants without regard to protected characteristics such as race, religion, gender, sexual orientation, gender identity or expression, national origin, disability, age, veteran status, marital status, pregnancy-related conditions, and other legally protected categories. It also references its EEO policy, workplace discrimination rights information, belonging resources, and hiring information.

The posting says that applicants who need an accommodation can use Google’s accommodations form. It also states that Google does not accept agency resumes and will not pay fees for unsolicited resumes sent by agencies or other parties.

On compensation-related equity, the posting explains that any equity grant is handled solely at Alphabet’s discretion under the relevant stock plan and grant agreement. It also says such grants are not guaranteed, depend on approval, and do not affect statutory payments or create an acquired right based on past awards.

Applicants are told that information collected through Google Careers and any submitted application is subject to Google’s Applicant and Candidate Privacy Policy.

Degree Requirement: Bachelor’s

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