Forward Deployed Engineer, GenAI, Google Cloud

As a GenAI Forward Deployed Engineer at Google Cloud, you will bridge the gap between frontier AI products and production-grade reality for customers. You will act as a builder-consultant, coding, debugging, and shipping bespoke agentic solutions within customer environments. The role involves managing blockers to production such as integration complexities, data readiness, and state-management issues, while providing deployment of AI systems and feedback to Google Cloud's product roadmap.

• Bachelor’s degree in Engineering, Computer Science, a related field, or equivalent practical experience.
• 2 years of experience building and shipping production-grade AI-driven solutions 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 such as Google Cloud Platform (GCP).
• Experience building pipelines for structured and unstructured data, incorporating vector databases and retrieval-augmented generation (RAG)-like architectures.

Preferred qualifications:

• Master’s degree or PhD in AI, Computer Science, or a related technical field.
• Experience implementing multi-agent systems using frameworks like LangGraph, CrewAI, or Google’s Agent Development Kit (ADK) and patterns such as 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.

• 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 the 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 an equal opportunity workplace and affirmative action employer 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. Qualified applicants are considered regardless of criminal histories, consistent with legal requirements. Accommodations for applicants with disabilities are available upon request.