Partner Forward Deployed Engineer, GenAI, Google Cloud
Mumbai, Maharashtra, Indiaonsitefull timeToday
Responsibilities:
Serve as a team lead and developer within the strategic AI partner for complex AI applications, working with the partner’s own teams to transition from rapid prototypes to production-grade, replicable agentic workflows (e.g., multi-agent systems, Model Context Protocol (MCP) servers) that drive measurable Return on Investment (ROI).
Provide the guidance and insight to be the connective tissue between Google’s AI products, the partner’s and customer's live infrastructure, including Application Programming Interfaces (APIs), legacy data silos, and security perimeters as part of an expert team.
Build high-performance evaluation pipelines and observability frameworks to ensure partner developed agentic systems meet rigorous requirements for accuracy, safety, and latency.
Co-build with a strategic AI partner’s own forward deployed engineering teams to instill Google-grade development best practices, ensuring long-term project success and high end-user adoption.
Minimum qualifications:
Bachelor's degree or equivalent practical experience.
8 years of experience in software development.
7 years of experience leading technical project strategy, Machine Learning (ML) design, and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
5 years of experience with design and architecture; and testing/launching software products.
2 years of experience with GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (e.g., language modeling, computer vision).
Preferred qualifications:
Master’s or PhD in AI, Computer Science, or a related technical field.
Experience implementing multi-agent systems using frameworks (e.g., LangGraph, CrewAI, Agent Development Kit (ADK)) and complex 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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