AVP, GenAI Enterprise Architect

• Role Overview: Design and deploy enterprise-grade AI solutions (LLMs, RAG, agents) by
• selecting appropriate models, building data pipelines, and integrating them with cloud platforms
• (AWS, Azure, GCP). Lead technical strategies, ensure scalability, manage AI security/
• hallucinations, and bridge business needs with engineering teams.

Key Responsibilities

• System Design & Architecture: Architect end-to-end Generative AI systems, including
• retrieval-augmented generation (RAG) and vector data systems.
• Model Selection & Tuning: Evaluate and select cutting-edge commercial (e.g., GPT-4) and
• open-source models, and fine-tune models for domain-specific use cases.
• LLMOps & Pipelines: Establish LLMOps standards for model versioning, evaluation, prompt
• management, and CI/CD, ensuring robust, production-grade AI.
• Integration & Security: Integrate AI solutions with existing APIs, applications, and databases
• while enforcing security, privacy, and guardrails to manage hallucinations and adversarial
• attacks.
• Strategic Leadership: Collaborate with stakeholders to map business challenges to AI
• solutions and establish AI governance frameworks.
• Bachelor’s / Master’s in Computer Science, AI, Data Science, or related field;
• 8–15 years in software engineering, ML, or AI roles. Experience with enterprise-level systems.