GenAI Architect

Position Summary

The Senior AI Architect is responsible for designing and implementing advanced AI and cloud architectures, with a strong emphasis on integrating generative AI technologies. This role requires a broad understanding of AI and cloud platforms, along with the ability to engage with customers on a variety of architectural topics in both cloud and data center environments.

The ideal candidate is passionate about GenAI and AI technologies, stays current with industry trends, and drives innovation within the organization and for clients. As a senior leader, you will interact frequently with customers, provide expert opinions, and contribute to HCL’s strategic vision.

Key Responsibilities

Technical & Engineering Leadership

• Design and implement AI and cloud architectures, integrating GenAI technologies to enhance functionality and scalability.

• Lead architectural discussions with clients, providing expert guidance on best practices for AI and cloud integration.

• Ensure solutions align with microservice and container-based environments across public, private, and hybrid clouds.

• Contribute to HCL’s thought leadership in the Cloud Native domain with a strong understanding of open[1]source technologies (e.g., Kubernetes/CNCF) and partner technologies.

• Collaborate on technical projects with global partners, including Google, Microsoft, AWS, IBM, Red Hat, Intel, Cisco, and Dell/VMware.

Service Delivery & Innovation

• Develop GenAI solutions from ideation to MVP, ensuring high performance and reliability within cloud[1]native frameworks.

• Optimize AI and cloud architectures to meet client requirements, balancing efficiency and effectiveness.

• Evaluate existing complex solutions and recommend architectural improvements to transform applications with cloud-native/12-factor characteristics.

• Promote the adoption of GenAI technologies within cloud-native projects, driving initiatives that push the boundaries of AI integration in cloud services.

Thought Leadership and Client Engagement

• Provide architectural guidance to clients on incorporating GenAI and machine learning into their cloud[1]native applications and architectures.

• Conduct workshops, briefings, and strategic dialogues to educate clients on AI benefits and applications, building strong, trust-based relationships.

• Act as a trusted advisor, contributing to technical projects (PoCs and MVPs) with a 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 cloud architecture.

• Create and record videos to share insights and opinions on AI and cloud technologies, enhancing HCL’s industry leadership.

Collaboration and Multi-Customer Management

• Engage with multiple customers simultaneously, providing high-impact architectural consultations and

fostering strong 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

• Experience: 8+ years in cloud and AI architecture design, 5+ years in software development.

• Technologies: Proficiency in Python, Java (and/or Golang), and Spring; expertise in AWS, Azure, Google Cloud; Kubernetes and containerization.

• AI Expertise: Advanced machine learning algorithms, GenAI models (e.g., GPT, BERT, DALL-E, GEMINI), NLP techniques.

• Big Data: Experience with Hadoop and Spark.

• Ethics: Knowledge of AI ethics and governance.

• Methodologies: Agile and Scrum project management.

Desired Skills & Experience

• Deep knowledge of machine learning operations (MLOps) and experience in deploying, monitoring, and maintaining 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.

• Knowledgeable about AI ethics and bias mitigation, with experience in implementing strategies to ensure air and unbiased AI solutions.

• Serverless Computing and Distributed Systems

• Deep Learning Frameworks (TensorFlow, PyTorch)

• Innovation and Emerging Technology Trends

• Strategic AI Vision and Roadmapping

• Enthusiastic about working in a fast-paced environment using the latest technologies, and passionate about HCL’s dynamic and high-energy Labs atmosphere.

Verifiable Certification

• At least one recognized cloud professional certification (AWS Certified Solutions Architect, Google Professional Cloud Architect, or Microsoft Certified: Azure Solutions Architect Expert)