You will design the blueprints for our AI ecosystem—selecting models, designing RAG (Retrieval-Augmented Generation) pipelines, and ensuring our AI initiatives are scalable and ethical
Job Summary
You will design the blueprints for our AI ecosystem—selecting models, designing RAG (Retrieval-Augmented Generation) pipelines, and ensuring our AI initiatives are scalable and ethical.
Architect end-to-end GenAI solutions, including model selection (LLMs, SLMs, Multi-modal), vector database orchestration, and API integration.
Implement "AI Guardrails" to manage hallucination, data leakage, and prompt injection risks.
Matching Summary
You will design the blueprints for our AI ecosystem—selecting models, designing RAG (Retrieval-Augmented Generation) pipelines, and ensuring our AI initiatives are scalable and ethical.
Skills & Requirements
Must-have
Generative AI solutions design
Retrieval-Augmented Generation (RAG)
LLM, SLM, Multi-modal model selection
Vector database orchestration
Python development with FastAPI/Flask
AWS Bedrock and Google Vertex AI
Nice-to-have
Scalable and ethical AI initiatives
High-performance inference pipelines
Cost optimization for AI solutions
Agile methodologies and DevOps practices
Key Requirements
3+ years as Solution Architect with AI/ML exposure
Expertise in LangChain
Hands-on experience with Gemini, Claude, Llama 3, Mistral
Proficiency with Graph & Vector DBs
Experience with Docker, Kubernetes
Bachelor's or Master's degree in CS, Engineering, AI