Description

Architect enterprise-grade Generative and Agentic AI solutions, designing scalable cloud-native architectures and autonomous agent systems.

This role is remote.

Responsibilities

• Design and implement RAG pipelines, multimodal AI applications, and multi-agent systems.
• Build scalable cloud-native AI architectures using AWS Bedrock, Azure OpenAI, or GCP Vertex AI.
• Implement vector search and knowledge retrieval frameworks with tools like Pinecone, Weaviate, FAISS, and ChromaDB.
• Lead model selection, evaluation, and deployment strategies while establishing GenAIOps/LLMOps best practices.
• Ensure AI security, compliance, and governance standards across all deployed solutions.

Required Skills

• 13+ years of experience in software engineering and AI architecture.
• Advanced proficiency in Python, Pandas, and PyTorch.
• Hands-on experience with Generative AI, Agentic AI, and LLM frameworks (LangChain, LlamaIndex, LangGraph).
• Expertise in Multi-Agent frameworks such as CrewAI and AutoGen.
• Deep understanding of RAG (Retrieval-Augmented Generation) and Prompt Engineering.
• Experience with vector databases (Pinecone, Weaviate, FAISS, ChromaDB).
• Cloud AI services: AWS Bedrock, Azure OpenAI, or GCP Vertex AI.
• Proficiency in building REST APIs using FastAPI, Flask, or Spring Boot.
• Containerization and orchestration with Docker and Kubernetes.
• CI/CD pipelines and MLflow for model monitoring.

Preferred Skills

• Experience with Hugging Face and Scikit-Learn.
• Background in AI Governance, Security, and Compliance.

Key Skills

Education

Bachelor's degree