E-Solutions

E-Solutions

Sr. Google Cloud Platform AI Engineer Location : Irving, TX, or Charlotte (100% Onsite)

Charlotte, North Carolina, USA · Senior · Part-time

Sponsorship not specifiedDetected 54 days ago
PythonJavaFastAPISpringVector DatabasesGCPCloud PlatformsDockerKubernetesLLMsRAGAgentic AILangGraphCollaboration

About the role

  • We are seeking an innovative and highly skilled AI Engineer to join our dynamic team.
  • The ideal candidate will bridge the gap between traditional software engineering and cutting-edge artificial intelligence.

Responsibilities

  • 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.

Requirements

  • 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.
  • 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).
  • Strong proficiency in both Java and Python, with a proven track record of building production-grade software.
  • Familiarity and practical experience with the Model Context Protocol (MCP) for standardizing AI interactions with external tools.

Skills

  • Irving, TX, or Charlotte (100%
  • 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).
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This listing is sourced directly from E-Solutions's careers page and normalized into a canonical job model.