AI Architect
4 weeks ago
About Us
Infosys is a global leader in next-generation digital services and consulting. We enable clients in more than 50 countries to navigate their digital transformation. With over four decades of experience in managing the systems and workings of global enterprises, we expertly steer our clients through their digital journey. We do it by enabling the enterprise with an AI-powered core that helps prioritize the execution of change. We also empower the business with agile digital at scale to deliver unprecedented levels of performance and customer delight. Our always-on learning agenda drives their continuous improvement through building and transferring digital skills, expertise, and ideas from our innovation ecosystem.
Role Definition:
AI Architects design the overall structure of AI systems, ensuring they are scalable, secure, and aligned with business goals. They define technical roadmaps and oversee the implementation of AI projects.
Skills:
Proficient:
o Languages/Framework: Fast API, Azure UI Search API (React)
o Cloud: Azure Cloud Basics (Azure DevOps)
o Gitlab: Gitlab Pipeline
o Ansible and REX: Rex Deployment
o Data Science: Prompt Engineering + Modern Testing
o Data mining and cleaning
o ML (Supervised/unsupervised learning)
o NLP techniques, knowledge of Deep Learning techniques include RNN, transformers
o AI integration and deployment
o AI frameworks (PyTorch)
o AI/MLOps frameworks
o Model deployment processes
o Data pipeline monitoring
• Expert: (in addition to proficient skills)
o Languages/Framework: Azure Open AI
o Data Science: Open AI GPT 4/3, Embeddings + Vector Search
o Databases and ETL: Azure Storage Account
o Deep understanding of AI/ML algorithms and their applications
o Expertise in system design and architecture patterns
o Expertise in End-to-end AI solution delivery
o Knowledge of cloud-native AI solutions and microservices
o Familiarity with AI ethics, bias mitigation, and explainability
o Strong communication skills to collaborate with stakeholders
o Experience with AI deployment pipelines (MLOps)
o Knowledge of AI ethics frameworks and guidelines (e.g., EU AI Act, IEEE Ethically Aligned Design)
o Understanding of bias detection and mitigation techniques
o Familiarity with explainable AI (XAI) methods
o Strong understanding of data privacy laws (GDPR, CCPA)
o Ability to conduct AI impact assessments
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