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AI/ML Tower Head

2 weeks ago

Kolkata, West Bengal, India Quantum Business Advisory (QBA) Full time

Job Title: AI/ML Tower Head

Location: Kolkata

Experience: 12+ years overall, with at least 7+ years in Data Science / AI / ML leadership

Reports To: Head of Digital / CTO / Delivery Head

Note: We will prefer someone with a shorter 'Notice Period'

Role Overview:

The AI/ML Tower Head will lead the Artificial Intelligence and Machine Learning vertical, driving strategy, solution development, and delivery excellence across enterprise projects. This role is responsible for establishing AI/ML capabilities, nurturing a strong technical team, managing client engagements, and ensuring business growth through innovative data-driven solutions.

Key Responsibilities:

1. Understanding of the Role & Mandate

  • Be ready to articulate your approach to owning an AI Agents vertical end-to-end.
  • Explain how you would plan the first 3060 days, including delivery timelines for multiple production-ready agents.
  • Be prepared to discuss architecture ownership, scalability, security, and performance considerations.

2. Technical Depth (AI/ML + Agents + Systems)

  • Brush up on agent frameworks, LLM orchestration, retrieval pipelines, and multi-agent systems.
  • Prepare to discuss previous work building or integrating production-grade AI/ML solutions.
  • Expect questions on MLOps, deployment, monitoring, and optimization.
  • Be ready to explain how you evaluate model performance and ensure reliability.

3. Leadership & Delivery Capability

  • Prepare examples of leading cross-functional teams (engineering, product, data).
  • Highlight moments where you delivered high-impact outcomes under tight timelines.
  • Show clarity on how you drive architecture decisions, code quality, and delivery pipelines.

4. Strategic Contribution

  • Understand how AI innovation ties to IP creation, compliance, and long-term product strategy.
  • Think through how government or regulated environments influence AI design decisions.
  • Be prepared to share ideas on scaling agents for enterprise/government-grade reliability.

5. Problem-Solving & Vision

  • Expect scenario-based questions (e.g., How would you design X agent in 4 weeks?").
  • Be ready with a crisp vision for AI agents over the next 12–18 months—architecture, automation, and business impact.
  • Prepare to articulate your approach to risk mitigation, data governance, and quality control.

6. Communication & Stakeholder Management

  • Demonstrate how you communicate complex AI topics to non-technical leadership.
  • Be ready to walk through your decision-making style and how you handle escalations

    Required Skills & Qualifications:
  • Proven experience in managing large AI/ML programs in enterprise environments.
  • Hands-on expertise in Python, TensorFlow, PyTorch, Scikit-learn, MLflow, and data visualization tools.
  • Strong understanding of cloud platforms Azure, AWS, or GCP.
  • Familiarity with GenAI tools and LLM frameworks (OpenAI, LangChain, Hugging Face, etc.).
  • Excellent leadership, communication, and stakeholder management skills.
  • Prior experience in setting up AI CoE or delivery tower is highly desirable.

Preferred Certifications:

  • Microsoft Certified: Azure AI Engineer Associate / Data Scientist Associate
  • AWS Certified Machine Learning Specialty
  • Google Professional Machine Learning Engineer
  • Executive Program in AI/ML from reputed institutions (IIM, ISB, Stanford, etc.)