Senior Consultant Business Consulting (AI Architect)

Role Overview: As an AI Architect Senior Consultant at Infosys Global Consulting, you will be leading the design and implementation of cutting-edge AI solutions for clients across various industries. Your role will involve driving innovation and ensuring the scalability, security, and compliance of AI systems. Key Responsibilities: - Designing AI Systems: Lead the architectural design for AI solutions, including Generative AI and Conversational AI, while ensuring adherence to Responsible AI guidelines. - Model Deployment: Deploy robust AI/ML models on Cloud-based and on-premises infrastructures, optimizing performance for real-world applications. - Decision-Making: Select appropriate AI models, tools, and technologies for implementation. - Technical Guidance: Guide the team in identifying optimized solutions for client needs, leveraging expertise in NLP, LLMs, and Computer Vision. - Best Practices & Innovation: Implement AI/ML best practices, data governance, and ethical considerations to drive innovation. - Collaboration: Work closely with data scientists, cross-functional teams, IT teams, and leadership to align AI solutions with business goals. - Risk & Futureproofing: Address risks related to data privacy, ethics, compliance, and ensure AI systems are ready for emerging trends. - Client Engagement: Spend 60% of the time on client engagements, providing AI architecture design for client solutions, managing multiple projects concurrently. - Practice Contributions: Dedicate 40% of the time to anchoring/driving RFP responses, architecture design for internal solutions, meeting clients, building PoVs/offerings, and coaching team members. Qualification Required: - Experience: At least 7 to 8 years of experience in AI architecture design, deploying AI solutions in large-scale environments, and working with leading AI-focused companies or top consulting firms. - Skills: Proficiency in AI Frameworks such as TensorFlow, PyTorch, Keras, ML Ops/LLM Ops, Cloud Expertise, Machine Learning, Deep Learning, Programming languages like Python, R, Java, and Data Management with big data technologies.,