Chief AI Innovation Officer

2 weeks ago

Ghaziabad, Uttar Pradesh, India beBeeArchitecture Full time ₹ 1,50,00,000 - ₹ 2,50,00,000
AI Systems Architect

Job Description:

We are seeking a visionary AI architect to lead the design and integration of cutting-edge AI systems, including generative AI, large language models, multi-agent orchestration, and retrieval-augmented generation frameworks.

This role demands a strong technical foundation in machine learning, deep learning, and AI infrastructure, along with hands-on experience in building scalable, production-grade AI systems on the cloud.

The ideal candidate combines architectural leadership with hands-on proficiency in modern AI frameworks and can translate complex business goals into innovative, AI-driven technical solutions.

Key Responsibilities:

  • Architect and oversee implementation of scalable and secure AI systems leveraging LLMs, GenAI, and multi-agent frameworks to support diverse enterprise use cases (e.g., automation, personalization, intelligent search)
  • Design and implement retrieval-augmented generation pipelines integrating vector databases, LLMs, and proprietary knowledge bases
  • Build robust agentic workflows using tools like LangGraph, CrewAI, or Agno, enabling autonomous task execution, planning, memory, and tool use
  • Collaborate with product, engineering, and data teams to translate business requirements into architectural blueprints and technical roadmaps
  • Define and enforce AI/ML infrastructure best practices, including security, scalability, observability, and model governance
  • Manage technical roadmap, sprint cadence, and 3–5 AI engineers, coach on best practices
  • Lead AI solution design reviews and ensure alignment with compliance, ethics, and responsible AI standards
  • Evaluate emerging GenAI & agentic tools; run proofs-of-concept and guide build vs-buy decisions

Required Skills and Qualifications:

  • 9+ years of experience in AI/ML engineering or data science, with 2+ years in AI architecture or system design
  • Proven experience designing and deploying LLM-based solutions at scale, including fine-tuning, prompt engineering, and RAG-based systems
  • Strong understanding of agentic AI design principles, multi-agent orchestration, and tool-augmented LLMs
  • Proficiency with cloud-native ML/AI services and infrastructure design across AWS, GCP, or Azure
  • Deep expertise in model lifecycle management, MLOps, and deployment workflows (batch, real-time, streaming)
  • Familiarity with data governance, AI ethics, and security considerations in production-grade systems
  • Excellent communication and leadership skills, with the ability to influence technical and business stakeholders

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