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.
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