What are the responsibilities and job description for the AI Engineer RAG Model & Google Cloud Platform position at Apex 2000?
Job Details
Job Title - AI Engineer – RAG Model & Google Cloud Platform
We are looking for an experienced AI Engineer with expertise in Retrieval-Augmented Generation (RAG) models, Gemini AI, and vector databases. The ideal candidate should have a strong understanding of AI workflows, proficiency in Google Cloud Platform (Google Cloud Platform) services like BigQuery,GKE,Dataproc,Dataflow and Composer, and a keen eye for cost optimization and innovation.
Key Responsibilities:
- Design, develop, and optimize RAG models using Gemini AI and other LLM frameworks.
- Implement and manage vector databases to enhance AI-driven retrieval efficiency.
- Develop AI/ML solutions leveraging Python, TensorFlow, and other deep learning frameworks.
- Ensure seamless integration of AI solutions with Google Cloud Platform services like BigQuery, Cloud Fuction,GKE and cloud-based tools.
- Drive cost optimization strategies for AI workloads on Google Cloud Platform.
- Research and implement innovative ideas to enhance AI capabilities and automation.
- Collaborate with cross-functional teams to align Cloud Cost optimization & AI solutions with business goals.
Tech Skills:
- AI & ML Frameworks: RAG Model, Gemini AI, TensorFlow, PyTorch
- Programming Languages: Python, SQL
- Cloud Platforms: Google Cloud Platform (Google Cloud Platform), BigQuery, Vertex AI, AI Platform
- Data Processing: Airflow, Apache Beam, Kafka
- Databases: Vector Databases (e.g., Pinecone, FAISS, Weaviate), PostgreSQL
- Infrastructure & DevOps: CI/CD Pipelines, Terraform, Docker, Kubernetes
- Cost Optimization: Cloud resource optimization strategies, serverless computing
Required Skills & Qualifications:
- Strong expertise in RAG models and Gemini AI for AI-driven applications.
- Hands-on experience with vector databases and AI-based retrieval systems.
- Proficiency in Python, TensorFlow, and other AI/ML frameworks.
- Solid understanding of machine learning, deep learning, and NLP concepts.
- Experience working with Google Cloud Platform services, including BigQuery,GKE,Dataproc,Dataflow and Composer and cloud optimization techniques.
- Ability to design and deploy cost-efficient AI solutions in a cloud environment.
- Strong problem-solving skills and a passion for innovation in AI and cloud computing.
Preferred Qualifications:
- Experience in LLMs (Large Language Models) and generative AI frameworks.
- Familiarity with MLOps, CI/CD pipelines, and cloud-based model deployment.
- Previous experience in optimizing AI workloads on Google Cloud Platform and other cloud platforms.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
