About the Role:

We are looking for an accomplished Director of Data Engineering, AI & Full Stack Engineering to lead the technology vision, architecture, and execution of data-intensive and AI-powered products.

This is a senior engineering leadership position for an experienced technology leader who can operate across Data Engineering, Artificial Intelligence, Backend, Full Stack Development, Cloud, and Product Engineering.

Key Responsibilities:

- Define and execute the engineering strategy across Data Engineering, AI/ML, Backend, and Full Stack product development.

- Lead the architecture and development of scalable, cloud-native data platforms and AI-powered product capabilities.

- Drive the adoption of Generative AI, LLMs, Agentic AI, RAG, AI-powered automation, and intelligent product experiences.

- Own the design of enterprise-grade data architectures supporting high-volume structured and unstructured data.

- Build and scale modern data engineering platforms covering batch processing, streaming, data integration, data modeling, data quality, governance, and observability.

- Lead the development of AI/ML platforms and production-grade machine learning pipelines in partnership with Data Science and AI teams.

- Drive MLOps practices covering model deployment, inference, monitoring, governance, experimentation, and continuous improvement.

- Oversee development of backend and full-stack applications that consume data and AI capabilities.

- Establish scalable API, microservices, event-driven, and distributed system architectures.

- Drive engineering standards around architecture, coding practices, testing, security, performance, reliability, and maintainability.

- Partner closely with Product, Design, Data Science, Analytics, Security, and Business leadership to translate product strategy into technology roadmaps.

- Build, mentor, and scale high-performing engineering teams across multiple technical disciplines.

Required Skills & Experience :

- 15 - 20 years of experience in software engineering, data engineering, AI/ML engineering, or product technology leadership.

- Strong experience leading large-scale engineering organizations and complex product development initiatives.

- Deep understanding of modern data engineering, distributed systems, cloud platforms, and software architecture.

- Strong hands-on understanding of AI/ML, Generative AI, LLMs, RAG, Agentic AI, and AI application architectures.

- Strong experience with Python, SQL, distributed processing, data platforms, and modern engineering practices.

- Strong backend and full-stack engineering understanding with experience in APIs, microservices, databases, and cloud-native applications.

- Experience designing and scaling highly available, secure, and performance-sensitive systems.

- Strong understanding of DevOps, CI/CD, observability, infrastructure automation, and production engineering.

Preferred Qualifications :

- Experience building technology products for SaaS, Enterprise Software, FinTech, HealthTech, E-commerce, or other technology-driven product organizations.

- Experience taking AI/ML products from concept and experimentation through production and large-scale adoption.

- Master's degree in Computer Science, Engineering, Artificial Intelligence, Data Science, or a related discipline is desirable.