Job Description & Details
This is a serious lead-level AI role focused on migrating, scaling, and architecting agentic AI systems in a hybrid enterprise environment. If you are tired of building simple wrapper apps and actually want to build production-grade autonomous agents and migrate complex architectures to Google Cloud Platform, this gig gives you the ownership to do just that.
What You'll Actually Be Doing
Your day-to-day will be a mix of hands-on architecture, full-stack coding, and leading cloud migrations. You will take ownership of existing AI and machine learning applications, refactor them, and transition them directly into a Google Cloud Platform ecosystem. You will be knee-deep in building agentic RAG workflows, tying together Python backend services with React frontends, and making sure that token usage and GCP infrastructure costs stay optimized while pushing the boundaries of what these LLMs can automate.
The Core Tech Stack
You need absolute fluency in Python for backend ML work and React for the user-facing interfaces. On the AI side, knowing how to string together Large Language Models, semantic search, and multi-agent systems via frameworks using concepts like MCP and Agentic RAG is non-negotiable. Relational databases like MS SQL Server and MySQL are daily drivers, and you must know your way around GCP native AI/ML services and BigQuery to estimate costs and operationalize pipelines.
Interview Expectations
Expect the engineering panel to drill down into how you architect agentic workflows and handle failure states when an LLM hallucinates mid-task. They will likely ask you to whiteboard how you would design a self-correcting RAG pipeline that minimizes API latency while maximizing context relevance. The interviewer is secretly testing your production battle-scars—they want to see if you actually know how to debug non-deterministic AI outputs rather than just talking about theoretical prompt engineering.
Application Advice
Your resume needs to skip the generic buzzwords and immediately highlight concrete numbers around LLM orchestration, GCP cloud migrations, and full-stack Python/React implementations. Make sure keywords like Agentic RAG, MCP, BigQuery, and semantic search are clearly visible in your experience bullets to ensure you clear the ATS filters and grab the hiring manager's attention right away.