AI Architect
Job Description
- Configure and manage Generators to create dynamic, personalized system responses based on user input and contextual data.
- Architect and manage Datastores to persist session and user data, supporting adaptive and context-driven interactions.
- Collaborate with backend developers, business analysts, UX designers, and QA teams to ensure seamless integration of conversational logic with APIs, databases, and business processes.
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Key Skills
About Company
Skills:
Rest Apis, FastAPI, Python, Generative AI, LLMs, Gemini, Enterprise Knowledge Systems, Prompt Engineering, Llama, Semantic Kernel, Multi-Agent Systems, Microservices architecture, Azure OpenAI, Azure AI Services, RAG, CrewAI, AWS Bedrock, Embeddings, LangGraph, Cloud-based AI platforms, AI governance, GPT, Claude, Responsible AI practices, Vector Databases, AutoGen, Observability, Agentic AI, Security
Skills:
Predictive Analytics, Sql, Uipath, SAP BTP, Nlp, AI architecture, LLMs, Vector databases, SAP Signavio, Azure AI, RAG, AWS Bedrock, CrewAI, AIOps, Celonis Process Intelligence, LangGraph, Enterprise observability, Microsoft Agent Framework, Knowledge graph, ETL pipelines, Streaming data lakes, Business AI Platform, SNOW assist, Agent skills, GCP Vertex AI
Skills:
Node.js, Backend Development, Gcp, Cloud Infrastructure, Azure, Ocr, Python, AWS, PDF processing, Stripe payments, LLMs AI APIs, SaaS products, webhook handling, Document Analysis
Skills:
Kubernetes, Java, Scalability, Containers, React, Machine Learning, System Design, Node.js, Data Services, Javascript, Databases, Application Performance, Microservices, Testing, Python, Software Architecture, Apis, messaging systems, Security, scalable cloud applications, DevOps practices, cloud cost efficiency, infrastructure as code, Reliability, Production Operations, full-stack software engineering, observability, Distributed Applications, enterprise integrations