GEN AI Architect

We are seeking an experienced AI/ML & Generative AI Solution Architect to design, architect, and lead the implementation of enterprise-scale Artificial Intelligence (AI), Machine Learning (ML), and Generative AI solutions. This role will partner with business stakeholders, engineering teams, and clients to develop scalable, secure, and responsible AI solutions that drive business value and innovation. The ideal candidate has deep expertise in AI/ML architecture, cloud platforms, Generative AI technologies, MLOps, and modern software engineering practices. Key Responsibilities Design and architect end-to-end AI/ML and Generative AI solutions aligned with business and technology objectives. Define scalable, secure, and high-performing solution architectures utilizing cloud platforms such as Microsoft Azure, Amazon Web Services (AWS), or Google Cloud Platform (GCP). Lead the design and implementation of Generative AI solutions leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), prompt engineering, and related AI technologies. Translate business requirements into technical architectures, solution blueprints, design specifications, and architecture diagrams. Develop AI solution frameworks covering data ingestion, model development, deployment, monitoring, and lifecycle management. Establish and implement MLOps best practices, including CI/CD pipelines, model versioning, automated testing, deployment, and governance processes. Architect secure, scalable, and cost-effective AI platforms utilizing microservices, APIs, and containerization technologies. Evaluate, recommend, and implement appropriate AI/ML and Generative AI approaches based on business requirements, data availability, and solution complexity. Collaborate with data engineering teams to integrate AI solutions with enterprise data platforms, pipelines, ETL/ELT processes, and analytics ecosystems. Facilitate client discussions, solution workshops, architectural reviews, and technical presentations. Define and promote standards, best practices, reference architectures, and coding guidelines for AI solution development. Ensure solutions align with Responsible AI principles, including fairness, transparency, explainability, privacy, security, and risk management. Provide technical leadership, mentoring, and guidance to engineering and data science teams. Monitor solution performance, identify risks, troubleshoot issues, and recommend optimizations for reliability, scalability, and cost efficiency. Stay informed on emerging AI technologies, industry trends, tools, and frameworks to support continuous innovation. Required Qualifications Bachelor's degree in Computer Science, Information Technology, Engineering, Data Science, or a related field, or equivalent practical experience. Proven experience designing and architecting enterprise AI/ML solutions. Strong expertise in Generative AI technologies, including LLMs, RAG architectures, prompt engineering, and AI evaluation methodologies. Experience with cloud platforms such as Azure, AWS, or GCP. Knowledge of MLOps frameworks, CI/CD practices, model deployment, monitoring, and governance. Experience designing distributed systems, microservices-based architectures, and containerized solutions. Strong understanding of data engineering concepts, data pipelines, and enterprise data platforms. Excellent communication, presentation, stakeholder management, and problem-solving skills. Preferred Qualifications Advanced degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related discipline. Experience with AI governance, Responsible AI frameworks, and model risk management. Industry certifications related to cloud platforms, AI, machine learning, or solution architecture. Experience working in client-facing consulting, professional services, or enterprise architecture roles. Required Technical Skills Mandatory Skills Generative AI Retrieval-Augmented Generation (RAG) Prompt Engineering MLOps Cloud Platforms (Azure, AWS, or GCP) Preferred Skills PythonLangChain, LlamaIndex, Semantic Kernel, or similar frameworks Vector Databases Docker and Kubernetes Data Engineering and ETL/ELT CI/CD Tools and DevOps Practices We are an Equal Opportunity Employer and are committed to creating an inclusive environment for all employees. Employment decisions are based on business needs, job requirements, and individual qualifications, without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected characteristic under applicable law. #J-18808-Ljbffr Galent