Role Description
The Principal Software Engineer is a highly skilled expert responsible for shaping and executing the organization’s intelligence vision. This role integrates expertise in Artificial Intelligence (AI), Machine Learning (ML), Automation, Data Analytics and Visualization to deliver transformative customer, partner, and colleague experiences that drive revenue growth and enhance productivity.
The position defines the technical direction for intelligence initiatives, leading the design, development, and deployment of robust, scalable, and secure AI solutions while fostering innovation through emerging technologies.
A critical aspect of the role is providing partnership, mentorship and technical guidance, cultivating a culture of excellence and continuous learning. Through close cross-functional collaboration across teams and stakeholders, the role ensures technical efforts are strategically aligned and deliver measurable impact. Additionally, the position plays a central role in strategic problem-solving, addressing complex challenges in intelligence systems and data pipelines, and making informed architectural decisions that ensure long-term scalability and success.
Responsibilities
- Define, drive, and communicate the technical vision for intelligence, AI, and data initiatives, ensuring alignment with CIT strategy, EPD goals, and broader organizational objectives.
- Take a holistic view of CIT systems and architecture to ensure they are scalable, reliable, secure, and maintainable over multiple years.
- Lead the design, development, and deployment of high performance AI systems, data pipelines, and intelligent services from conception through production.
- Make strategic architectural decisions to address complex AI, data, and platform challenges, balancing short term delivery with long term resilience and scalability
- Identify opportunities to simplify systems, reduce operational and security risk, and improve developer productivity.
- Contribute directly to prototyping, proof of concepts, and implementation of technical components when needed to validate strategy, de risk decisions, or accelerate progress.
- Architect, evolve, and scale AI, automation, and intelligence platforms that enable advanced analytics, personalization, search, and intelligent decision making.
- Drive innovation in intelligence models, distributed training, optimization techniques, and data engineering to maximize performance, quality, and business impact.
- Enhance search and discovery capabilities using intelligent algorithms, natural language processing, an