Director - Data Engineering, AI & Full Stack
First seen by Alion on Sep 9, 2026.
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.
Skills
IT Head, Data Engineering, Full Stack, AI Integration, Python, SQL, Native Cloud, Distributed Systems, Microservices Architecture