Solution Architect - Generative Ai

Airbus

Bangalore, India
Generative ai solution design
Rag pipeline architecture
Llm and slm model selection
Design end-to-end GenAI solutions including model selection, vector database orchestration, and API integration

Job Summary

  • Design end-to-end GenAI solutions including model selection, vector database orchestration, and API integration.
  • Build robust Retrieval-Augmented Generation architectures to connect LLMs with proprietary data and implement AI Guardrails.
  • Optimize token usage and compute costs while rapidly building Proofs of Concept (PoCs) for new AI features.

Matching Summary

Design end-to-end GenAI solutions including model selection, vector database orchestration, and API integration.

Skills & Requirements

Must-have

  • Generative AI solution design
  • RAG pipeline architecture
  • LLM and SLM model selection
  • Vector database orchestration
  • High-performance inference pipelines
  • Python development with FastAPI/Flask
  • AWS Bedrock and Google Vertex AI

Nice-to-have

  • Scalable and ethical AI initiatives
  • AI Guardrails implementation
  • Cost optimization for AI solutions
  • Agile methodologies and DevOps practices
  • Containerization with Docker/Kubernetes

Key Requirements

  • 3+ years as Solution Architect with AI/ML exposure
  • Expertise in LangChain framework
  • Hands-on experience with Gemini, Claude, Llama 3, Mistral
  • Proficiency with Graph & Vector Databases
  • Strong Python skills
  • Experience with AWS Bedrock and Google Vertex AI
  • Understanding of SDLC, Agile, and DevOps
  • Experience with Docker and Kubernetes
  • Bachelor's or Master's degree in CS, Engineering, AI, or related field

Work Rights

Not specified

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