Responsible AI Engineer Manager/Senior Manager

Accenture•St. Louis, MO

2d•$80,400 - $293,800

About The Position

Accenture’s Global Responsible AI team within the Global Data & AI Practice helps organizations design, build, and deploy AI that earns trust and complies with laws, regulations, and ethical norms. The team develops Responsible AI intellectual property and solutions with ecosystem partners, engages with regulators, conducts research with academia, and provides client training and resources through the Responsible AI Academy. The Responsible AI Engineer develops advanced AI models and solutions for business challenges while incorporating responsible AI considerations such as fairness, transparency, explainability, robustness, soundness, and privacy. The role supports clients in identifying and mitigating AI risks, contributes to the full AI development lifecycle, and helps establish internal responsible AI practices. Client-facing work, sales conversations, and proposal preparation may be part of the role. Travel may be required, varying from 0% to 100% based 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: at least 12 years; an associate degree requires at least 6 years of work experience.
At least 5 years of experience developing and evaluating machine learning models and AI solutions, including experience in at least two of the following areas: statistics and probability theory, regression modeling, 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 fundamental 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 such as AWS, Azure, or Google Cloud as they relate to AI.
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.
At least one year of experience addressing responsible AI aspects such as fairness, transparency, explainability, robustness, soundness, and privacy; preferably in a client-facing environment.

Nice To Haves

Additional coursework or training in responsible AI, technology ethics, or related fields.
Certifications in AI, machine learning, or data science.
Prior experience on ethical AI or AI-for-social-good projects.
Knowledge of AI ethics, data privacy, and regulatory frameworks.
Experience with AI model interpretability and explainability tools.
Experience with specialized visualization techniques or tools 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, focusing on ethical and responsible practices.
Identify, evaluate, and apply relevant Responsible AI dimensions, including bias, fairness, robustness, and explainability, and help mitigate identified risks.
Support client sales conversations and proposal preparation.
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 responsible AI guidelines, 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.