Responsible AI Engineer Manager/Senior Manager

Accenture•Chicago, IL

About The Position

Accenture’s Global Responsible AI team within the Global Data & AI Practice works with organizations to ensure AI is designed, built, and deployed in ways that engender trust and adhere to laws, regulations, and ethical norms. The team develops Responsible AI strategies, intellectual property, and solutions with ecosystem partners; engages regulators on policy; conducts research with academia; and provides client training and resources through the Responsible AI Academy. The Responsible AI Engineer develops advanced models to address business challenges while applying Responsible AI principles, including fairness, transparency, explainability, robustness, soundness, and privacy. In this client-facing role, the engineer helps clients identify and manage AI risks and works with colleagues to deliver technically sound, equitable, and responsible AI solutions. Responsibilities span the full AI development lifecycle, from data preparation and design through coding, testing, deployment, and support. The role also contributes to client sales and proposals, internal guidance and training, documentation, and the ongoing optimization of AI systems. Travel may be required, ranging from 0% to 100% depending on business needs and client requirements.

Requirements

Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field, or equivalent work experience; the posting specifies a minimum of 12 years of work experience as an alternative. With an associate’s degree, a minimum of 6 years of work experience is required.
At least 5 years of experience developing and evaluating machine learning models and AI solutions.
At least 2 areas of experience among statistics and probability theory, regression modelling, clustering methods, time-series forecasting, tree ensembles, deep learning, neural networks, generative AI, natural language processing, text mining, computer vision, image recognition, or machine learning visualization tools.
At least 5 years of experience with programming languages such as Python, R, or Java.
At least 5 years of experience with AI and machine learning frameworks such as Scikit-learn, TensorFlow, or PyTorch.
At least 5 years of experience with rapid API development using frameworks and tools such as Django, Flask, or FastAPI.
At least 5 years of experience with version-control practices and platforms such as GitHub or Bitbucket.
At least 5 years of experience with database management and data processing.
At least 5 years of experience with cloud services and platforms related to AI, such as AWS, Azure, or Google Cloud.
At least 5 years of experience working with complex datasets and performing data preprocessing and analysis.
Strong problem-solving and analytical skills.
Ability to collaborate in a team environment and communicate effectively with team members.
Commitment to ethical AI development and continuous learning.
Ability to manage multiple projects and priorities in a fast-paced environment.
Excellent documentation and presentation skills for technical and non-technical audiences.

Nice To Haves

Additional courses or training in Responsible AI, technology ethics, or related areas.
Certifications in AI, machine learning, or data science.
Experience on projects focused on ethical AI or AI for social good.
Knowledge of AI ethics, data privacy, and regulatory frameworks.
Experience with AI model interpretability and explainability tools.
Experience with specialized visualization techniques such as D3.js or ggplot.
Project management experience.
Business-level proficiency in a language other than English.

Responsibilities

Develop and implement AI models and solutions using ethical and responsible practices.
Identify, evaluate, and apply relevant Responsible AI dimensions, including bias, fairness, robustness, and explainability, and mitigate identified risks.
Support client sales conversations and prepare proposals.
Optimize and maintain existing AI systems to improve performance and adherence to ethical standards.
Participate in the full AI development lifecycle, including data preparation, design, coding, testing, deployment, and support.
Contribute to internal guidelines, responsible AI development best practices, and technical training.
Stay current with AI trends, ethical considerations, and technological advancements.
Help identify and correct biases in datasets and AI models.
Document AI development processes and maintain transparent records of decisions and methodologies.