AI Engineer (Gen AI, Gcp/ snowflake/aws)
AI Engineer (Gen AI, Gcp/ snowflake/aws)
Infosys LimitedEarly Applicant
- Posted 14 hours ago
- Be among the first 20 applicants
Job Description
Job Description:
- AI Engineer DBRX AWS Azure GCP Snowflake variants
- Core Skills
- Python SQL ETL ELT Data Modeling Data Quality Cloud native Development API Integration Data Engineering ETL Document Processing Workflow design knowledge of LLM development RAG
- Prompt Engineering AI Coding Assistants
- Advanced Skills
- RAG Data Pipelines LLM Data Integration AI Service Integration Scalable AI Deployments Agent Orchestration Tool Calling LangGraph LangChain
- Semantic Layers Data Governance Memory Management Autonomous Agents Agent Routing State Management Memory Handling Tool Integration
Key Responsibilities:
- Design develop and deploy Generative AI applications using LLMs and foundation models
- Develop AI solutions utilizing RAG Retrieval Augmented Generation architectures
- Build and optimize AI pipelines using Python LangChain LlamaIndex and vector databases
- Integrate AI solutions with AWS GCP and Snowflake environments
- Fine tune and evaluate LLMs for domain specific business use cases
- Create scalable APIs and microservices for AI model deployment
- Collaborate with data engineers ML engineers and business stakeholders
- Implement prompt engineering techniques and model performance optimization
- Ensure data security governance and compliance in AI applications
- Monitor and improve AI model performance in production environments
Technical Requirements:
- Strong programming experience in Python
- Hands on experience with Generative AI LLMs Prompt Engineering and RAG
- Experience with frameworks such as
- LangChain
- LlamaIndex
- Hugging Face
- OpenAI APIs
- Vertex AI Bedrock
- Strong cloud experience in AWS or GCP
- Hands on experience with Snowflake including data integration and optimization
- Experience with vector databases such as Pinecone FAISS ChromaDB or Weaviate
- Knowledge of REST APIs microservices and containerization Docker Kubernetes
- Familiarity with MLOps and CI CD practices

