Posted on: 29/10/2025
Description :
Qualifications & Experience :
- Masters 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.
- Proven track record in architecting and scaling AI/ML platforms, leading hands-on teams, and operating systems in production at scale.
- In the past few years, delivered end-to-end GenAI solutions with deep expertise in transformer architectures, GPU optimization, LLM data preparation, fine-tuning, evaluation, and deployment.
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 outcomedriven product strategy and prioritization.
Responsibilities :
- Define and lead AI platform technology strategy, driving innovation across agentic, lowcode 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 highpotential 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.
Product Strategy & Vision :
- Define and implement scalable product roadmaps leveraging advanced ML, LLM, and agentic systems.
- Build and deploy cross-cutting products that bridge multiple financial domains and enable high-impact business outcomes.
Did you find something suspicious?