Manager - AI Architect at KPMG Nederland

Bangalore, karnataka, India -

Full Time

Start Date

Immediate

Expiry Date

09 Feb, 26

Salary

0.0

Posted On

11 Nov, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

AI Architecture, Software Architecture, C#, Python, Machine Learning, Data Engineering, Cloud Technologies, Agile Project Management, Containerization, CI/CD, Data Ingestion, Model Training, Monitoring Systems, Versioning, Scalability, Security Best Practices, Quality by Design

Industry

Business Consulting and Services

Description

As AI Architect at KPMG You will be an accomplished individual contributor. You will specialize in helping our team’s driving innovation, accelerating the adoption of cutting-edge technologies, and enhancing our engineering practices. You will be known for having skills in software architecture embedding AI into it and will work across our teams to help them build and adopt common architectures and tooling w.r.t AI tools and technologies. You should be self-motivated, capable of writing code, and passionate about building scalable, high-quality software solutions. Responsibilities:s Work on the Implementation and Solution delivery of the AI applications leading the team across onshore/offshore and should be able to cross-collaborate across all the AI streams. Design end-to-end AI applications, ensuring integration across multiple commercial and open source tools. Work closely with business analysts and domain experts to translate business objectives into technical requirements and AI-driven solutions and applications. Partner with product management to design agile project roadmaps, aligning technical strategy. Work along with data engineering teams to ensure smooth data flows, quality, and governance across data sources. Lead the design and implementations of reference architectures, roadmaps, and best practices for AI applications. Fast adaptability with the emerging technologies and methodologies, recommending proven innovations. Identify and define system components such as data ingestion pipelines, model training environments, continuous integration/continuous deployment (CI/CD) frameworks, and monitoring systems. Utilize containerization (Docker, Kubernetes) and cloud services to streamline the deployment and scaling of AI systems. Implement robust versioning, rollback, and monitoring mechanisms that ensure system stability, reliability, and performance. Ensure the implementation supports scalability, reliability, maintainability, and security best practices. Have Quality by Desgin mindset and approach Expertise on C# or Python Expertise in ML and understanding, fine tuning LLMs/SLMs Qualifications: Bachelor’s/Master’s degree in Computer Science Certifications in Cloud technologies – Azure Hands on knowledge of Fabric

Responsibilities

Lead the implementation and solution delivery of AI applications while collaborating across teams. Design end-to-end AI applications and ensure integration across various tools and technologies.