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Senior AI Engineer / Senior Generative AI Engineer

STAFFXPERT LLCUnited States🇺🇸United StatesPosted 24 Aug 2026

Why This Role Stands Out

This hybrid role offers a fantastic opportunity to lead the development of cutting-edge Generative AI solutions, leveraging LLMs, RAG, and agentic frameworks. You'll thrive here if you're a seasoned AI professional eager to build scalable, production-ready applications and contribute to innovative projects within a collaborative environment. Apply now to shape the future of AI-driven enterprise solutions!

Quick Overview

Seniority
Mid Senior
Work mode
Hybrid
Location
United States
Posted
1 week ago
DockerAWSMLOpsAzureGenerative AIKubernetesLLMPythonREST

Job Description

Job Title Senior AI Engineer (Generative AI)

 

Job Summary

This role is ideal for a hands-on AI professional who is passionate about building and deploying enterprise-scale Generative AI solutions. The successful candidate will play a key role in designing, developing, and implementing AI-powered applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Agentic AI frameworks, and cloud-native technologies.

The ideal candidate combines strong software engineering expertise with practical experience delivering production-ready AI solutions that drive business value and innovation.


Key Responsibilities

  • Design, develop, and deploy scalable AI and Generative AI applications in production environments.

  • Build and maintain LLM-powered solutions using modern AI platforms and frameworks.

  • Develop Retrieval-Augmented Generation (RAG) solutions leveraging vector databases and enterprise knowledge sources.

  • Implement Agentic AI workflows using frameworks such as LangChain and LangGraph.

  • Create and integrate RESTful APIs to enable AI capabilities across business applications.

  • Collaborate with cross-functional teams to gather requirements and deliver AI-driven solutions.

  • Optimize AI applications for performance, scalability, reliability, and cost efficiency.

  • Conduct prompt engineering, model evaluation, testing, and continuous improvement of AI systems.

  • Deploy and manage applications using containerization and orchestration technologies such as Docker and Kubernetes.

  • Support MLOps practices including model deployment, monitoring, and lifecycle management.

  • Stay current with emerging AI technologies and contribute to innovation initiatives.


Required Qualifications

  • Bachelor''s or Master''s degree in Computer Science, Engineering, Artificial Intelligence, Data Science, or a related field.

  • 7+ years of software engineering experience with a strong development background.

  • 3+ years of hands-on experience building and deploying AI/ML or Generative AI solutions.

  • Strong proficiency in Python and modern software development practices.

  • Experience developing AI applications using:

    • OpenAI

    • Azure AI Services

    • AWS Bedrock

    • LangChain

    • LangGraph

    • Vector Databases (e.g., Pinecone, Chroma, Weaviate, FAISS)

  • Experience building and consuming REST APIs.

  • Hands-on experience with Docker and Kubernetes.

  • Knowledge of cloud platforms such as Azure and AWS.

  • Experience implementing RAG architectures and AI agent frameworks.

  • Strong analytical, troubleshooting, and problem-solving skills.

  • Excellent communication and collaboration abilities.


Preferred Qualifications

  • Experience working within automotive, manufacturing, or industrial environments.

  • Knowledge of Industry 4.0 initiatives and enterprise digital transformation programs.

  • Experience with MLOps, CI/CD pipelines, and AI application monitoring.

  • Familiarity with AI governance and responsible AI practices.

  • Cloud or AI-related certifications.


Required Skills

  • Generative AI

  • Large Language Models (LLMs)

  • Retrieval-Augmented Generation (RAG)

  • Agentic AI

  • Python

  • OpenAI

  • Azure AI

  • AWS Bedrock

  • LangChain

  • LangGraph

  • Vector Databases

  • REST APIs

  • Docker

  • Kubernetes

  • Cloud Technologies (Azure/AWS)

  • MLOps

  • Prompt Engineering

  • AI Application Development

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