Data Engineer
Summary
Design and operate scalable AI infrastructure for training and inference of generative models, optimizing performance, cost, and reliability while collaborating with cross-functional teams.
Overview
As an AI Infrastructure Engineer at Accenture, you will help design and operate scalable, reliable platforms that enable large-scale training and inference of generative AI solutions. You will work independently on defined deliverables while collaborating with cross-functional teams to solve complex engineering challenges and contribute to enterprise-grade AI platforms. This role offers opportunities to deepen technical expertise, grow into a subject matter specialist, and influence how Accenture delivers next-generation AI solutions for clients.
Responsibilities
- Architect, build, and implement infrastructure to support large-scale training and inference of generative AI models
- Design and optimize infrastructure for performance, scalability, cost efficiency, and responsible resource consumption
- Evaluate AI infrastructure options (cloud, platform, and tooling) and provide data-driven recommendations
- Advise on technology and vendor selection to align with business and strategic objectives
- Develop operational controls, monitoring, and observability solutions for AI platforms
- Implement control towers to monitor, manage, and improve generative AI platform operations
- Collaborate with engineering, architecture, and delivery teams to support end-to-end AI solutions
Required Qualifications
- Advanced proficiency in Python, with strong hands-on experience using the Pandas library
- Solid understanding of database architecture and data management concepts
- Minimum of 1 year of experience in relevant technology, data, or platform engineering roles
- Bachelor’s Degree in Computer Science, Engineering, Data Science, or a related field
- Ability to work independently while contributing effectively in team-based problem solving
- Strong analytical, communication, and documentation skills
Preferred Qualifications
- Knowledge of advanced data architecture principles
- Experience in platform engineering or infrastructure automation
- Exposure to Tableau or other data visualization tools
- Familiarity with technology architecture blueprints and roadmap definition