Forward Deployed Engineer, Generative AI, Google Cloud

Brak informacji o wynagrodzeniu

MidOn-site·WarszawaFull-time

#471258·Dodano 5 dni temu·2

Źródło: Google

Aplikuj teraz

Tech Stack / Keywords

Python LLMsMulti-ModalLarge Vision ModelsDevOpsMLOpsLangGraphCrewAIGoogle ADKMCP

Podsumowanie oferty

As an AI Forward Deployed Engineer at Google Cloud Consulting, you will build and deploy enterprise-grade AI applications for customer accounts, moving solutions from prototypes to production. You will develop agentic workflows and connect Google’s AI products with customers’ infrastructure.

Wymagania

Minimum qualifications:

Bachelor’s degree in Computer Science, a related technical field, or equivalent practical experience.
2 years of experience with software development programming in Python, or 1 year of experience with an advanced degree.
2 years of experience with Generative AI techniques (e.g., LLMs, Multi-Modal, and Large Vision Models) or with Generative AI-related concepts (language modeling and computer vision).
Experience implementing DevOps and MLOps pipelines.

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, or Google’s ADK) and complex patterns like ReAct, self-reflection, and hierarchical delegation.
Knowledge of LLM-native metrics (tokens/sec, cost-per-request) and techniques for optimizing state management and granular tracing.
Proven ability to implement secure agentic workflows incorporating MCP, tool-calling, and OAuth-based authentication.

Obowiązki

Serve as the lead developer for complex AI applications, transitioning from rapid prototypes to production-grade agentic workflows (e.g., multi-agent systems, MCP servers) that drive measurable Return on Investment (ROI).
Architect and code the connective tissue between Google’s AI products and customers’ live infrastructure, including APIs, legacy data silos, and security perimeters.
Build high-performance evaluation (Eval) pipelines and observability frameworks to ensure agentic systems meet 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 formal product feature requests for the 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.

Benefity

15% bonus target.
Equity.

Premie

Udziały pracownicze

Inne informacje

In most instances, the hiring process requires in-person interviews.

Google

56 aktywnych ofert

Zobacz wszystkie oferty

Aplikuj teraz