Responsible AI Solutions Architect
Job Description
Job Title: Responsible AI Solutions ArchitectLocation: London
Salary : CompetitiveSalary +Package(dependenton experience)
Career Level: (Accenture will be recruiting at the following levels : Associate Manager or Specialist) Travel: May be required for this role. The amount of travel will vary depending on business need and client requirements. Accenture is a leading global professional services company, providing a broad range of services in strategy and consulting, interactive, technology and operations, with digital capabilities across all of these services. With our thought leadership and culture of innovation, we apply industry expertise, diverse skill sets and next-generation technology to each business challenge. We believe in inclusion and diversity and supporting the whole person. Our core values comprise of Stewardship, Best People, Client Value Creation, One Global Network, Respect for the Individual and Integrity. Year after year, Accenture is recognized worldwide not just for business performance but for inclusion and diversity too. “Across the globe, one thing is universally true of the people of Accenture: We care deeply about what we do and the impact we have with our clients and with the communities in which we work and live. It is personal to all of us.” - Julie Sweet, Accenture CEO You are: We are seeking experts in architecting AI systems with a Responsible AI background, with a passion for being practical and hands on, designing and operationalizing responsible by design systems. As a Responsible AI technical solutions architect, you’ll be experienced in building state-of-the-art systems to solve difficult business challenges. You’ll also have experience specifying, designing and testing for functional and non-functional requirements of AI systems that can translate organizational or regulatory driven governance goals and objectives into technical design parameters to address responsible AI aspects such as AI model Fairness, Transparency, Explainability, Robustness, Soundness and Privacy - preferably gained in a client-facing environment. You’ll bring diverse expertise in architecture, software development and data engineering with specialization in RAI. Your experience will include how to develop technical approaches to AI governance for different classes of AI, and you’ll be dept at explaining how the responsible AI technical response needs to adapt to ML, Gen AI LLM models and services, agentic systems. You’ll be an outstanding technical specialist with the strong communication skills needed to liaise with your clients and your colleagues. The work: Some of the areas you’ll be working in include:
- Developing capability frameworks, reference designs, architecture patterns, requirements specification (FR/NRF’s), blueprints, and guides for designing and architecting AI systems from a responsible AI specialist perspective
- Working with Accenture AI and data teams, as well as partners, to embed/integrate responsible design approaches into the overall development lifecycle, workflow, technical stack, service/product model and platform/application design and delivery
- Decomposing and translating governance concepts and requirements, spanning regulatory/legal requirements, organizational policy, standards and controls into technical controls, and embedded within the SDLC, data and AI lifecycle.
- Developing best practices and architectural guidelines for AI model development, testing, deployment, and monitoring; including helping define, build and roll out our internal Responsible AI tools and assets.
- Creating methodologies and controls to support audit and assurance of AI systems to identify and mitigate issues such as biases, ensuring fairness and transparency.
- Creating test patterns, frameworks and testing processes for testing of AI systems. Developing test harnesses for red teaming, adversarial testing, and evaluation of multi-modal AI systems
- Spearheading Responsible AI related technology thought leadership and PoV, staying abreast of emerging technologies.
- Providing technical leadership and mentorship to AI development teams, and development and delivery of Responsible AI technical training.
- Facilitating communication between technical and non-technical stakeholders regarding AI projects and their impact.
- Leading the evaluation of third-party Responsible AI tools and frameworks
- Supporting client sales conversations and proposal preparation
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or related technical fields.
- Architectural experience with cloud platforms (e.g., AWS, Azure, Google Cloud) and their AI services
- Hands on experience with models and services provided by Google, Open AI, Anthropic etc, and the eval/assurance/testing approaches they provide
- Experience with 3rd party GRC tooling and products such as Service Now and OneTrust.
- Proficiency in AI and machine learning algorithms and frameworks (e.g., TensorFlow, PyTorch).
- Experience in developing and deploying machine learning models and AI solutions. At least 2 from the following: Statistics and Probability, Regression Modelling, Clustering Methods, Neural Networks, Deep Learning, Time Series Forecasting
- Demonstrable applications of the above models including but not limited to Natural Language Processing, Text Mining, Computer Vision, Image Recognition, , Machine Learning Visualization and Interpretability
- Strong programming skills in languages such as Python, R, or Java.
- Experience with big data technologies (e.g., Hadoop, Spark) and database management systems.
- Specific technology domain areas experience in at least one of: software development, cloud computing, systems engineering, data & analytics.
- Knowledge of ethical AI principles, data privacy laws, and regulatory requirements.
- Knowledge of existing and emerging Standards for AI safety and assurance e.g UK Government standards, ISO, IEEE, NIST...
- Proven track record in leading, scaling and delivering complex AI projects.
- Experience in implementing AI solutions in large-scale, enterprise environments.
- Strong leadership and team management skills.
- Excellent problem-solving and analytical abilities.
- Effective communication skills, capable of conveying complex AI concepts to diverse audiences.
- Commitment to ethical AI practices and continuous learning.
- Ability to work under pressure and manage multiple projects simultaneously.
- Additional courses or training in areas related to responsible AI, ethics in technology, or similar fields are beneficial.
- Certifications in AI, machine learning, or related fields.
- Experience with Data & AI in specific domains (e.g., healthcare, finance, retail).
- Familiarity with AI model explainability and interpretability tools.
- Understanding of MLOps, LLMOps and DevOps practices, including CI/CD pipelines, for AI systems.
- Containerization capabilities such as Docker and Kubernetes.
- Linguistic proficiency (to a reasonable business level) in a language other than English
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