AI Architect
Experience: 10+ years in web application development/DevOps, with 5+ years in AI system design and cloud-native architecture.
Job Purpose:
Design and lead scalable AI solutions that optimize eLearning development, automate content creation, improve productivity, and enhance learning experiences through Generative AI and automation.
Key Responsibilities:
- Lead AI strategy and design end-to-end AI architecture for eLearning and enterprise solutions.
- Design and implement LLM, RAG, and Agentic AI solutions using frameworks such as LangChain or Semantic Kernel.
- Architect AI-powered text, audio, video, and image generation capabilities.
- Design secure and scalable cloud architectures on AWS, Azure, or GCP.
- Define data architecture, governance, security, and Responsible AI practices.
- Drive MLOps/DevOps, including CI/CD, Docker, Kubernetes, monitoring, and model lifecycle management.
- Integrate AI solutions with LMS/LXP, CMS, CRM, SCORM, xAPI, and LTI platforms through APIs and microservices.
- Establish coding/API standards and conduct architecture and code reviews.
- Collaborate with AI, engineering, product, and business teams to deliver enterprise-grade solutions.
Key Skills:
- AI/GenAI: OpenAI/Claude, LLMs, Prompt Engineering, RAG, Agentic AI, LangChain/Semantic Kernel, Embeddings, Vector Databases.
- Backend: Python (FastAPI/Django) or Node.js, REST APIs, WebSockets, session/state management.
- Cloud: AWS/Azure/GCP with hands-on experience in secure, scalable deployments.
- DevOps: Docker, Kubernetes, CI/CD, GitHub Actions or equivalent.
- Database: PostgreSQL or equivalent + Vector DB such as Pinecone, Weaviate, or pgvector.
- Security: IAM, secrets management, encryption, data privacy, and secure AI architecture.
Qualification:
- Bachelors/Master’s in Computer Science, Engineering, Data Science, or equivalent experience.
- 5+ years of experience in AI system design.
- Hands-on experience with LLMs, RAG, Vector Databases, and API-based AI
📌 Artificial Intelligence Architect (Pune)
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