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.