Head of AI Platform Engineering and Product Stack

About the company : A Top IT Product Company

Requirements : Position Summary

■ Lead the strategic evolution of India's most sophisticated BFSI AI platform ecosystem, directing a 40-person engineering and data science team to deliver agentic platform capabilities through cutting-edge agentic tech stack where agent creation as well agent orchestration, AI native vertical focused workflows and journeys along with scalable AI / ML infrastructure.

Qualifications & Experience

■ Master’s or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or related from a globally ranked institution.

■ 12+ years driving large-scale enterprise apps, including 8+ years building enterprise AI platforms and delivering multi-product rollouts in a BFSI / fintech domain.

Skills

• Hands-on experience scaling AI / ML applications (e.g., Uvicorn, vLLM) in production.
• Advanced orchestration of large ML systems and agentic workflows end-to-end.
• Evaluation frameworks across classical ML and GenAI (task metrics, robustness, safety).
• Deep infrastructure understanding (GPU / CPU architecture, memory / throughput) and MLOps for model operationalization.
• Application architecture expertise : modular design, shared large-model services across multiple application components.
• Modern cloud proficiency : AWS, GCP (compute, networking, storage, security).
• Strong programming discipline and production deployment best practices.
• Team scaling & mentoring; effective cross-functional leadership.
• Business outcome–driven product strategy and prioritization.

Responsibilities :

■ Define and lead AI platform technology strategy, driving innovation across agentic, low-code and document science platforms, advanced LLM search, and next-gen financial products.

■ Architect multi-agent, autonomous workflow solutions and ensure scalable, resilient ML infrastructure to support cross-domain product delivery.

■ Create and own the technology roadmap aligned to strategic business goals and competitive market positioning.

■ Lead and scale the AI engineering and Data Science team from 40+, building organizational excellence in MLEs, MLOps, and data engineering.

■ Establish and champion best practices in AI governance, ethical frameworks, and business impact measurement.

■ Drive cross-functional stakeholder engagement, collaborating closely with product, design, data, and industry partners to accelerate platform innovation and industry leadership.

■ Represent the company as an authority on AI within industry forums, publications, and speaking events.

■ Foster a culture of continuous learning, mentorship, and innovation, developing high-potential AI talent for next-generation leadership.

■ Own and report platform success metrics, business impact KPIs, and deliver on ambitious product growth.

■ Example technical challenges : Design scalable document AI and agentic search workflows for high-volume BFSI use cases; deploy autonomous ML systems supporting real-time lending and regulatory compliance; orchestrate and optimize multi-agent workflows for financial products lifecycle.

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