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TD Newton
About the role
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Proposed designation:
Associate Director
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Role type:
Individual contributor
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Reporting to:
Director, Chief Architect
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Geo to be supported:
KPMG Delivery Network (KDN)
KPMG Delivery Network (KDN) is seeking an AI Technology Architect with deep expertise in AI technology to join our KDN AI Labs. This role is crucial for designing, architecting, and implementing advanced AI solutions t hat align with KDN’s strategic objectives. The AI Technology Architect will be responsible for the technical design and solution architecture of AI projects, working closely with development teams and being hands-on with the latest AI technologies.
This role requires not only leadership in technical design but also hands-on development skills, ensuring that the architect can lead by example and contribute directly to the coding, model development, and deployment processes.
Key responsibilities include:
1.
Solution Architecture and Technical Design:
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Design and architect end-to-end AI solutions, including data pipelines,
model development, deployment strategies, and integration with existing
systems.
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Define the technical components, services, and libraries required for AI
projects, ensuring scalability, security, and performance.
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Lead the selection of appropriate
AI frameworks, tools, and platforms (e.g., TensorFlow, PyTorch,
Databricks, Azure AI) to meet project requirements.
2.
Hands-On Development:
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Actively participate in the development of AI models, writing code,
building algorithms, and deploying models into production environments.
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Collaborate with data scientists and software engineers to implement AI
solutions that are robust, scalable, and efficient.
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Ensure that the technical design is aligned with best practices for AI
development, including the use of CI/CD pipelines, containerization
(Docker, Kubernetes), and cloud deployment (Azure).
3.
Technical Leadership:
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Provide technical guidance and mentorship to development teams, ensuring
that they follow best practices in AI and software development.
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Review code, design, and architecture to ensure that the solutions meet
KDN’s high standards for quality and security.
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Lead technical discussions in design and implementation phases, making
critical decisions that impact the architecture and design of AI
solutions.
4.
Component and Service Design:
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Architect and design reusable components, microservices, and APIs that can
be leveraged across multiple AI projects within KDN.
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Develop and maintain libraries of reusable code, tools, and templates that
accelerate AI development and ensure consistency across projects.
Ensure that all components are designed for integration with existing systems, supporting seamless data flow and interoperability.
5.
Research and Innovation:
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Stay up-to-date with the latest advancements in AI, machine learning, deep
learning, and cloud computing, bringing new ideas and technologies to the
team.
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Experiment with emerging AI technologies, such as Generative AI,
Reinforcement Learning, and Neural Architecture Search, to identify their
potential applications within KDN.
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Lead the technical exploration of new AI use cases, developing prototypes
and proof-of-concept solutions to validate their feasibility.
6.
Collaboration and Communication:
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Work closely with stakeholders across KPMG member firms to understand
business needs and translate them into technical solutions.
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Communicate complex technical concepts to non-technical stakeholders,
ensuring that they understand the capabilities and limitations of AI
technologies.
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Collaborate with external partners, including technology providers and
academic institutions, to drive innovation and knowledge sharing.
6.
Security and Compliance:
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Architect AI solutions with a strong focus on security, ensuring that data
privacy and protection are built into the design.
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Implement compliance with industry standards and regulations (e.g., GDPR,
ISO 27001), ensuring that AI solutions adhere to KDN’s legal and ethical
guidelines.
Educational qualifications
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Bachelor’s or Master’s degree in Computer Science, Engineering, Data
Science, or a related field.
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Advanced certifications in AI/ML, Cloud Computing, or Enterprise
Architecture are highly desirable.
Work experience
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12+ years of experience in software development, with at least 3 years
focused on AI, machine learning, or related technologies.
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Proven experience in architecting and implementing AI solutions,
including hands-on development with frameworks like TensorFlow, PyTorch,
Keras.
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Extensive experience with cloud platforms, particularly Microsoft Azure,
and expertise in deploying AI solutions in cloud environments.
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Strong background in DevOps practices, including CI/CD pipelines, Docker,
and Kubernetes.
Skills
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Deep understanding of AI/ML algorithms, model development, and
deployment strategies.
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Proficiency in programming languages such as Python, Java, or C++, with a
focus on AI/ML libraries and frameworks.
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Strong problem-solving skills, with the ability to design and implement
complex technical solutions.
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Excellent communication skills, with the ability to lead technical
discussions and collaborate with cross-functional teams.
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Knowledge of enterprise architecture frameworks (TOGAF) and ITIL
practices.