At Google Cloud, we are pivoting from standard cloud adoption to leading the "Agentic Era" of enterprise technology.
As an AI/ML Customer Engineer Specialist, you will engage with the most ambitious enterprises across the Nordic regions to redefine their business strategies through AI. You will act as a trusted AI advisor capable of commanding a room of executive decision-makers, and a highly skilled developer who can open a laptop and build state-of-the-art, machine-learning-powered systems. You will partner closely with strategic sales teams to lead proactive discovery, identify high-impact AI workloads, and design advanced architectures that drive measurable business outcomes.
In this role, you will step away from high-volume, superficial support and adopt a "fewer accounts, deeper technical execution" model, dedicating your technical expertise to a highly focused portfolio of strategic focus accounts. You will serve as the ultimate technical authority on integrating advanced generative AI and multi-agent orchestration systems into complex enterprise environments. You will own the customer's AI success journey end-to-end. By building continuous, long-term relationships with technical decision-makers and CXOs, you will earn a seat at the table as their primary AI strategist.
You will architect robust, data-connected solutions that move beyond simple chat interfaces. Crucially, once you have secured executive commitment and built high-impact prototypes, you will orchestrate seamless handovers within our Forward-Deployed Engineers (FDEs), who will bring your architectures into full-scale production.
Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
Sweden: kr1260000 - kr1300000 (SEK) + 42.86% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Initiate strategic conversations with customer CXOs, VPs, and technical decision-makers to identify complex AI workloads. Deliver workshops and rapid-prototyping sessions that influence leaders to change their technology roadmaps in favor of Google Cloud AI.
- Design, document, and execute an AI strategic technical plan for your focus accounts, guiding them through advanced AI maturity stages and successfully moving net-new use cases toward production.
- Build, code, and deploy functional, customer-tailored proofs-of-concept (POCs) and minimum viable products (MVPs). Maintain a Level 400 technical capability in agentic frameworks, enterprise architectures, and developer tools.
- Act as the technical bridge between the customer and Google's engineering resources. Refine initial requirements, prepare technical environments, and execute high-fidelity, documented handovers to Forward-Deployed Engineers (FDEs) for production deployment.
- Serve as "Customer Zero" by adopting newly released AI technology early (EAP, Public Previews). Identify, prioritize, and document customer feature requests, blockages, and platform gaps, maintaining a tight feedback loop with Google AI Product Management and Engineering to help shape the global AI roadmap.
Qualifications
Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 10 years of experience with cloud native architecture in a customer-facing or support role.
- Experience in architecting solutions that integrate AI models using agents with enterprise data sources using patterns like Retrieval-Augmented Generation (RAG), Text-to-SQL, and semantic search.
- Experience with search systems including retrieval, ranking, and search quality tuning.
- Experience coding in Python, JavaScript or TypeScript, Go, or Java to demo, prototype, or workshop integration patterns with customers.
- Experience presenting to technical stakeholders and executive leaders.
Preferred qualifications:
- Experience with iPaaS, Application Programming Interface (API) gateways, or Enterprise Service Buses (ESBs) in a cloud environment.
- Experience with functional evaluation metrics used to assess model quality and agent quality.
- Experience developing agents using frameworks such as LangGraph, Semantic Kernel, or the Google AI Agent Development Kit (ADK).
- Knowledge of observability constructs including distributed tracing, logging, and audit logging for AI applications.
- Knowledge of application integration governance and security, including OAuth2 flows and short-lived credential management.
- Understanding of integration patterns using OpenAPI and Model Context Protocol (MCP) to connect AI agents with business systems and API gateways.