AI Architect

Description & Requirements Position Summary The Principal AI Architect is responsible for leading the design and implementation of advanced AI solutions and strategic architecture. Working closely with technology leaders from across our global client community, you will be their senior Trusted Advisor for their AI-enabled transformation journey. This role demands deep understanding of AI and related technologies, running in Edge, on-prem and Public Cloud environments. Acting at the forefront of our industry you will be fully conversant with Generative AI, and its impact at both the individual employee and strategic organisational level. The ideal candidate will be an established thought-leader, with solid architectural and engineering credentials. Working ahead of industry trends, deeply passionate about technology-enabled business transformation and demonstrating a strong innovation-led posture. As a thought leader, you will interact frequently with CxO level clients, AI industry leaders, provide expert opinions, and contribute to HCL’s strategic vision. Key Responsibilities Technical & Engineering Leadership Design comprehensive AI solution and technology architecture, integrating latest AI technology developments into world‑class solutions. Lead high‑level architectural discussions with clients, providing expert guidance on best practices for AI implementations across AI PC, Edge, Data Centre and Public Cloud environments. Ensure solutions align with modern best practices across the full spectrum of platforms and environments. Deep understanding across GPU/NPU, Cognitive Infrastructure, Application and Copilot/agent domains. Contribute leadership in the AI & Cloud domains with a deep understanding of opensource technologies (e.g., Kubernetes, OPEA) and partner technologies. Collaborate on joint technical projects with global partners, including Google, Microsoft, AWS, NVIDIA, IBM, Red Hat, Intel, and Dell. Service Delivery & Innovation Architect innovative AI solutions from ideation to MVP, rapidly enabling genuine business value. Optimize AI and cloud architectures to meet client requirements, balancing efficiency, accuracy and effectiveness. Assess and review existing complex solutions and recommend architectural improvements to transform applications with latest AI technologies. Drive the adoption of cutting‑edge GenAI technologies spearheading initiatives that push the boundaries of AI integration across the full spectrum of environments. Thought Leadership and Client Engagement Provide expert architectural and strategy guidance to clients on incorporating Generative AI into their business and technology landscape. Conduct workshops, briefings, and strategic dialogues to educate clients on AI benefits and applications, establishing strong, trust‑based relationships. Act as a trusted advisor, contributing to technical projects with a strong focus on technical excellence and on‑time delivery. Author whitepapers, blogs, and speak at industry events, maintaining a visible presence as a thought leader in AI and associated technologies. Collaboration and Customer Engagement Engage with multiple customers simultaneously, providing high‑impact consultative relationships. Work closely with internal teams and global partners to ensure seamless collaboration and knowledge sharing across projects. Maintain a hands‑on technical credibility, staying ahead of industry trends and mentoring others in the organization. Mandatory Skills & Experience 10+ years architecture design 7+ years in software engineering Professional‑level expertise in Public Cloud environments (AWS, Azure, Google Cloud) Demonstrable coding proficiency with Python, Java or Go languages Advanced machine learning algorithms, GenAI models (e.g., GPT, BERT, DALL‑E, GEMINI), NLP techniques Working familiarity with Copilot solutions, in both software engineering and office productivity domains Exemplary verbal and written communication skills Agile and Scrum project management Desired Skills & Experience Knowledge of GenAI operations (LLMOps), experience governing AI models in production environments. Proficiency in data engineering for AI, including data preprocessing, feature engineering, and pipeline creation. Expertise in AI model fine‑tuning and evaluation, with a focus on improving performance for specialized tasks. Copilot design, engineering and extensions. Knowledgeable about Responsible AI, including governance and ethics. Bias mitigation, with experience in implementing strategies to ensure fair and unbiased AI solutions. Deep Learning Frameworks (TensorFlow, PyTorch) Innovation and Emerging Technology Trends Strategic AI Vision and Road mapping Enthusiastic about working in a fast‑paced environment using the latest technologies, and passionate about dynamic and high‑energy Lab culture. Verifiable Certification Recognized Professional certification from Google, Microsoft or AWS in an AI and/or Cloud‑related domain. #J-18808-Ljbffr