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Staff Forward Deployed Engineer, Developer AI, Google Cloud

Google
Bengaluru, IND
Senior · 8+ years experience
Onsite
Discovered 5 days ago
servicenow

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 (ROI).
  • 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.
  • Design and deploy production-grade agentic developer workflows on Google Cloud's AI stack, executing large-scale refactors, language migrations, Specification-to-Pull Request pipelines, and automated review/incident-to-fix loops.
  • Embed with customer's staff engineers and leaders to identify core SDLC bottlenecks, such as legacy migrations, test coverage, review latency, or onboarding friction, and define success metrics.
  • Integrate Google’s agentic systems into the customer's existing ISV and tools (e.g., Teamwork Graph, GitLab, ServiceNow, Slack) leveraging MCP and A2A protocols.

Minimum qualifications:

  • Bachelor’s degree in Engineering, Computer Science, a related field, or equivalent practical experience.
  • 8 years of experience in cloud computing or a technical customer-facing role.
  • Experience deploying, scaling, and debugging Large Language Model (LLM) or agent-based systems in production environments (including tools, memory, orchestration, evaluation, tracing, and cost/latency profiling).
  • Experience with end-to-end technical ownership of engineering projects with executive stakeholders.

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, Agent Development Kit (ADK)) and complex patterns (e.g., ReAct, self-reflection, hierarchical delegation).
  • Experience with agentic frameworks and harness layers, such as Google's Agent Development Kit (ADK) or equivalent, protocol-level interoperability (MCP, Agent-to-Agent (A2A)) across third-party Independent Software Vendor (ISV) platforms (e.g., ServiceNow), and security ecosystem in DevSecOps.
  • 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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