Generative AI Engineer

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About the Role

Generative AI Architect

Key Responsibilities Generative AI Architect :

• Architect and lead the design of

  GenAI solutions

  , including LLM integration, fine-tuning, and prompt engineering.
• Collaborate with product, data, and engineering teams to define and implement AI-driven strategies.
• Drive

  POC development

  and

  production deployment

  with a focus on scalability and performance.
• Evaluate emerging GenAI frameworks (LangChain, RAG, vector databases, etc.) and integrate them into enterprise systems.
• Define

  reference architectures

  ,

  reusable components

  , and

  AI adoption frameworks

  .
• Mentor AI/ML teams and ensure best practices in design and delivery.
• Stay updated on the latest trends in GenAI, NLP, and multimodal AI.

Key Responsibilities Lead Data Scientists:

• Lead end-to-end

  data science initiatives

  — from problem definition to deployment and performance monitoring.
• Develop advanced

  ML and AI models

  for pricing, underwriting, claims prediction, fraud detection, and risk scoring.
• Collaborate with business, engineering, and data teams for successful model implementation.
• Mentor and guide data scientists, ensuring model quality, explainability, and reproducibility.
• Communicate insights and technical outcomes to both technical and non-technical stakeholders.
• Stay up to date with emerging AI/ML and GenAI advancements to integrate into ongoing projects.