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Forward Deployed Engineer, Generative AI, Geo

Google
New York City, USA
Mid · 5+ years experience
Onsite
USD 152000-221000 / year
Discovered 3 days ago
python

Full Job Posting

Responsibilities

  • Serve as a developer for complex AI applications, transitioning from rapid prototypes to production-grade agentic workflows (e.g., multi-agent systems, Model Context Protocol (MCP) 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 as part of an expert team.
  • Build high-performance evaluation pipelines and observability frameworks to ensure agentic systems meet requirements for accuracy, safety, and latency.
  • Identify repeatable field patterns and friction points in Google’s AI stack, converting them into reusable modules or formal product feature requests for engineering teams.
  • Co-build with customer engineering teams to instill Google-grade development best practices, ensuring long-term project success and high end-user adoption.

Minimum qualifications:

  • Bachelor’s degree in Engineering, Computer Science, a related field, or equivalent practical experience.
  • 5 years of experience with software development using Python or similar coding languages.
  • Experience taking production-grade AI-driven solutions from conception to launch for customers.
  • Experience managing technical discovery sessions with customers.
  • Experience building pipelines for structured and unstructured data using both vector databases and Retrieval-Augmented Generation (RAG)-like architectures to power enterprise 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, ADK) and patterns (e.g., ReAct, self-reflection, hierarchical delegation).
  • Knowledge of LLM-native metrics (e.g., tokens/sec, cost-per-request) and techniques for optimizing state management and granular tracing.

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