Poland: zł280000 - zł287000 (PLN) + 15% bonus target + equity + benefits
Learn more about benefits at Google.
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.
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.
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.
