Posted May 7, 2026
Key Responsibilities:
Design and implement scalable, secure, and high-performance architectures for Generative AI applications. - Integrate Generative AI models into existing platforms, ensuring compatibility and performance optimization. - Fine-tune pre-trained generative models for domain-specific use cases. - Develop data pipelines, data integration, and data transformation solutions. - Stay updated with the latest advancements in Generative AI and recommend innovative applications for complex business problems. - Collaborate with cross-functional teams, including data scientists, engineers, and business stakeholders. - Mentor and guide team members on AI/ML best practices and architectural decisions. - Monitor the performance of deployed AI models and systems, ensuring robustness and accuracy. - Ensure compliance with ethical AI practices, data privacy regulations, and governance frameworks. - Implement safeguards to mitigate bias, misuse, and unintended consequences of Generative AI. Qualifications Required:
Bachelor's or masters degree in computer science, Data Science, or a related field. - 13+ years of relevant technical/technology experience, with significant expertise in GenAI projects with production deployment experience. - Advanced programming skills in Python and fluency in data processing frameworks like Apache Spark. - Strong knowledge of foundational models such as GPT-4 and Claude. - Proven track record with event-driven architectures and real-time data processing systems. - Familiarity with Azure DevOps and other LLMOps tools for operationalizing AI workflows. - Knowledge of containerization technologies such as Kubernetes and Docker. - Proficiency in cloud computing platforms such as Azure or AWS. - Exceptional leadership, problem-solving, and analytical abilities. - Superior communication and collaboration skills, with experience managing high-performing teams. Note: Nice to have skills include experience with additional technologies such as Datadog and Splunk, possession of relevant solution architecture certificates, and continuous professional development in data engineering and GenAI. Role Overview: As a GenAI Architect - Senior Manager at PwC US Acceleration Center, you will be responsible for designing and implementing scalable, secure, and high-performance architectures for Generative AI applications. Your role will involve fine-tuning pre-trained generative models, evaluating and deploying appropriate Generative AI frameworks, and staying updated with the latest advancements in Generative AI to recommend innovative applications for complex business problems. Additionally, you will collaborate with cross-functional teams, mentor team members on AI/ML best practices, and ensure compliance with ethical AI practices. Key Responsibilities:
Design and implement scalable, secure, and high-performance architectures for Generative AI applications. - Integrate Generative AI models into existing platforms, ensuring compatibility and performance optimization. - Fine-tune pre-trained generative models for domain-specific use cases. - Develop data pipelines, data integration, and data transformation solutions. - Stay updated with the latest advancements in Generative AI and recommend innovative applications for complex business problems. - Collaborate with cross-functional teams, including data scientists, engineers, and business stakeholders. - Mentor and guide team members on AI/ML best practices and architectural decisions. - Monitor the performance of deployed AI models and systems, ensuring robustness and accuracy. - Ensure compliance with ethical AI practices, data privacy regulations, and governance frameworks. - Implement safeguards to mitigate bias, misuse, and unintended consequences of Generative AI. Qualifications Required:
Bachelor's or masters degree in computer science, Data Science, or a related field. - 13+ years of relevant technical/technology experience, with significant expertise in GenAI projects with production deployment experience. - Advanced programming skills in Python and fluency in data processing frameworks like Apache Spark. - Strong knowledge of foundational models such as GPT-4 and Claude. - Proven track record with event-driven architectures and real-time data processing systems. - Familiarity with Azure DevOps
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