AI Architect
- Posted a month ago
- Over 100 applicants have applied
Job Description
Key deliverables:
- Develop AI automation scripts using Python and OpenAI API
- Deploy GenAI solutions and workflows in Azure
- Implement LLM-powered applications with Langchain
- Integrate AI tools with Azure Cognitive and Bot Services
Role responsibilities:
- Design and build scalable AI/ML models and pipelines
- Lead Azure-based GenAI deployments and orchestration
- Collaborate with data scientists and developers on solution design
- Optimize model performance and ensure reliability in production
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About Company
Skills:
Business Architecture, Solution Architect, Solution Architecture, Enterprise Architecture, Azure, Aws, Gcp, Cloud, Togaf, Ccsp, Flexcube, Oracle, Cissp, Mambo
Skills:
Machine Learning, Sql, Gcp, MLops, Azure, Python, AWS, Data lakes, LLM ecosystems, GenAI, Deep Learning frameworks, AI deployment frameworks, R, AI governance
Skills:
Java, PostgreSQL, Spring Boot, Kafka, Rabbitmq, Docker, Terraform, Sns, Restful Apis, Azure, Kubernetes, AWS, AWS SQS, Java Spring Framework, Microservices architecture, Palantir AIP, Palantir Foundry
Skills:
Java, Api Integration, Tensorflow, Pytorch, Gcp, Azure, Python, AWS, LangChain, Vector databases, Hugging Face, Pinecone, Llm, Gen AI, LangGraph, microservices architecture, FAISS, RAG, Weaviate
Skills:
snowflake , Agent2Agent (A2A), Model Context Protocol (MCP), Java, Gcp, Javascript, MLops, Sap Hana, Databricks, Azure, Python, AWS, Performance, ML model evaluation, SAP Business Data Cloud, AI coding tools, lakehouse patterns, knowledge graphs, Reliability, Security, coding agents, RAG, neuro-symbolic AI, cloud-native frameworks, agent orchestration, observability