cloudingest inc

Google Cloud Platform AI Engineer ---- Only W2

Irving, Texas, USA · full-time

Sponsorship not specified$40k-$60kDetected 56 days ago

PythonJavaFastAPISpringVector DatabasesGCPCloud PlatformsDockerKubernetesLLMsRAGAgentic AILangGraphCollaboration

About the role

We are seeking an innovative and highly skilled AI Engineer to join our dynamic team.
LLM Integration: Integrate cutting-edge Large Language Models (LLMs) into our core products and services to enhance functionality and user experience.

AI Agent Development: Design, build, and deploy autonomous AI agents capable of reasoning, planning, and executing complex workflows.
Automated Code Generation: Leverage AI and LLMs to build systems that assist in, or fully automate, code generation, testing, and optimization processes.
System Engineering: Write clean, scalable, and maintainable code in both Java and Python to support AI backend infrastructure.
Design, build, and deploy autonomous AI agents capable of reasoning, planning, and executing complex workflows.
Leverage AI and LLMs to build systems that assist in, or fully automate, code generation, testing, and optimization processes.
Write clean, scalable, and maintainable code in both Java and Python to support AI backend infrastructure.

Programming Languages: Strong proficiency in both Java and Python, with a proven track record of building production-grade software.
Google AI Tools: Hands-on experience with Google ADK (or equivalent Google Cloud AI/Vertex AI tools).
LLM Expertise: Deep comfort level and practical experience working with Large Language Models (prompt engineering, fine-tuning, RAG architectures).
MCP Knowledge: Familiarity and practical experience with the Model Context Protocol (MCP) for standardizing AI interactions with external tools.
Good-to-Have (Optional but highly valued): Experience with modern robust backend frameworks (e.g., Spring Boot for Java, FastAPI for Python).
Familiarity with containerization and orchestration (Docker, Kubernetes).
Experience with vector databases (e.g., Pinecone, Weaviate, Milvus).
The ideal candidate will bridge the gap between traditional software engineering and cutting-edge artificial intelligence.
Strong proficiency in both Java and Python, with a proven track record of building production-grade software.

Utilize the Model Context Protocol (MCP) to securely connect our AI models to various data sources, tools, and development environments.
Utilize Google ADK (AI Developer Kits) and related Google Cloud AI services (e.g., Vertex AI, Gemini APIs) to deploy robust AI solutions.
Hands-on experience with Google ADK (or equivalent Google Cloud AI/Vertex AI tools).

This listing is sourced directly from cloudingest inc's careers page and normalized into a canonical job model.