Role Overview :

We are seeking a Director of AI Engineering to lead the design, development, and deployment of AI-powered solutions across the organization.

This hands-on leader will build and manage a team of engineers and machine learning practitioners focused on developing AI capabilities that enhance our product offerings and drive efficiency across internal functions.

The role will be responsible for integrating AI into core products, enabling intelligent automation across business operations, and establishing scalable AI engineering practices across the company.

Key Responsibilities :

Build and Lead the AI Engineering Team :

- Build and manage a high-performing AI engineering team including GenAI engineers and applied AI developers.

- Establish best practices for AI development, deployment, and operations.

- Mentor engineers and promote a strong culture of experimentation and learning.

Develop AI-Powered Solutions :

- Lead the development of AI-driven capabilities across products and internal systems.

- Identify high-impact opportunities by partnering with business functions to apply Generative AI and automation.

- Translate business problems into AI-enabled engineering solutions.

Hands-On Technical Leadership :

- Actively contribute to architecture decisions, code reviews, and prototype development.

- Stay current with the rapidly evolving AI landscape and evaluate emerging tools, models, and frameworks.

- Build proof-of-concepts and lead technical spikes to de-risk new AI initiatives.

Drive AI Engineering Best Practices :

- Define standards for AI model/services selection, evaluation, and deployment.

- Establish governance practices for AI safety, security, and compliance.

- Ensure responsible AI development and proper handling of sensitive data.

Required Experience :

- 10+ years of experience in software engineering or AI/ML, with a strong hands-on track record in building production systems.

- 2- 3 years of direct experience working with LLMs, Generative AI, and prompt engineering techniques.

- Deep proficiency in Python and modern AI/ML frameworks (PyTorch, TensorFlow, Hugging Face).

- Solid understanding of agent-based systems, multi-agent orchestration, and autonomous workflows - with hands-on implementation experience.

- Hands-on experience with vector databases (Pinecone, Weaviate, Qdrant), RAG pipelines, and model evaluation frameworks.

- Experience designing and deploying production-grade ML pipelines and inference services.

- Proven ability to lead and grow engineering teams (5+ people).

- Strong foundation in classical ML/NLP (pre-LLM era) - understanding of model training, feature engineering, and evaluation methodologies.

Preferred Qualifications :

- Experience in the fintech or financial services domain.

- Hands-on experience with cloud AI services (AWS SageMaker).

- Background in AIOps practices - CI/CD for models, monitoring, drift detection.

- Published research, patents, or active contributions to the AI/ML community.

- Master's or PhD in Computer Science, AI/ML, or a related field