We are seeking a skilled Azure AI engineer with expertise in Strong programming skills in languages such as Python. Proficiency in AI/ML frameworks and libraries such as TensorFlow, PyTorch, or scikit-learn. Experience in OpenAI, LLaMA, Claude, Palm, Falcon large language models.
The Azure AI Engineer’s responsibility will be to design, develop, and implement Azure-based client solutions for global consulting. We are looking for a candidate with business technology and AI expertise who is passionate about building technology solutions to drive revenue, improve efficiency and reduce risk for both KPMG and its clients. The ideal candidate will have a strong understanding of Azure cloud services, as well as experience in software development and systems engineering.
Responsibilities:
- Work with senior SMPs across member firms to gather requirements / understand business purpose of solutions.
- Design and develop Azure-based solutions for global member firms (to provide to clients)
- Develop and implement Azure-based prototypes.
- Automate deployments, testing, and configuration management using tools like Azure DevOps, GitHub, and Ansible.
- Develop applications using Azure APIs and SDKs in .NET, Java, Python, Ruby, or other supported development languages.
- Understand and implement modern application development methodologies like microservices and serverless architectures on Azure.
- Design, develop, enhance, and deploy scalable AI solutions on various cloud platforms (both front end and back end), focusing on services like Vertex AI, Azure AI, and Google Studio.
- Commit source code via GitHub, Perform code reviews and sure code is up to date, complaint and free of vulnerabilities.
- Utilize development and operations tools, including Azure Studio and Copilot Studio, to enhance productivity and collaboration.
- Test and validate Azure-based solutions.
- Document Azure-based solutions
- Develop and implement data chunking strategies to handle large volumes of data efficiently during processing and analysis.
- Working with data scientists to gather and prepare data for MLOps pipelines.
- Optimize data storage solutions such as data lakes, leveraging cloud-based platforms like AWS S3, Azure Data Lake Storage, or Google Cloud Storage.
- Provide technical support to / respond to queries from global member firms on solutions.
Attributes:
- Strong problem-solving skills
- Ability to work independently and as part of a team
- Excellent communication and interpersonal skills
- Attention to detail
- Flexibility to join calls outside core working hours, as a member of an international team.
We are seeking a skilled Azure AI engineer with expertise in Strong programming skills in languages such as Python. Proficiency in AI/ML frameworks and libraries such as TensorFlow, PyTorch, or scikit-learn. Experience in OpenAI, LLaMA, Claude, Palm, Falcon large language models.
The Azure AI Engineer’s responsibility will be to design, develop, and implement Azure-based client solutions for global consulting. We are looking for a candidate with business technology and AI expertise who is passionate about building technology solutions to drive revenue, improve efficiency and reduce risk for both KPMG and its clients. The ideal candidate will have a strong understanding of Azure cloud services, as well as experience in software development and systems engineering.
Responsibilities:
- Work with senior SMPs across member firms to gather requirements / understand business purpose of solutions.
- Design and develop Azure-based solutions for global member firms (to provide to clients)
- Develop and implement Azure-based prototypes.
- Automate deployments, testing, and configuration management using tools like Azure DevOps, GitHub, and Ansible.
- Develop applications using Azure APIs and SDKs in .NET, Java, Python, Ruby, or other supported development languages.
- Understand and implement modern application development methodologies like microservices and serverless architectures on Azure.
- Design, develop, enhance, and deploy scalable AI solutions on various cloud platforms (both front end and back end), focusing on services like Vertex AI, Azure AI, and Google Studio.
- Commit source code via GitHub, Perform code reviews and sure code is up to date, complaint and free of vulnerabilities.
- Utilize development and operations tools, including Azure Studio and Copilot Studio, to enhance productivity and collaboration.
- Test and validate Azure-based solutions.
- Document Azure-based solutions
- Develop and implement data chunking strategies to handle large volumes of data efficiently during processing and analysis.
- Working with data scientists to gather and prepare data for MLOps pipelines.
- Optimize data storage solutions such as data lakes, leveraging cloud-based platforms like AWS S3, Azure Data Lake Storage, or Google Cloud Storage.
- Provide technical support to / respond to queries from global member firms on solutions.
Attributes:
- Strong problem-solving skills
- Ability to work independently and as part of a team
- Excellent communication and interpersonal skills
- Attention to detail
- Flexibility to join calls outside core working hours, as a member of an international team.
- 5+ years of experience in software development and systems engineering
- 4+ years of experience with Azure cloud services
- Experience with Azure DevOps
- Experience with Agile development methodologies
- Experience in building AI solutions (with preference for Generative AI solutions specifically)
- Bachelor's degree in computer science, information technology, or a related field desirable.
- Azure Solutions Architect Expert
- Azure Developer Associate
- Strong programming skills in languages such as Python
- Experience in OpenAI, LLaMA 2&3, Claude, Palm, Falcon large language models
- Strong proficiency in cloud platforms (AWS / Azure / Google Cloud Platform / IBM Cloud) and their specific AI services (Vertex AI, Azure AI, Google Studio)
- Experience in designing and optimizing data storage solutions using data lakes and cloud-based storage platforms (e.g., AWS S3, Azure Data Lake Storage, Google Cloud Storage).
- Familiarity with containerization technologies like Docker and orchestration tools such as Kubernetes for deploying and managing data pipelines.
- Experience with AI/ML frameworks and libraries such as TensorFlow, PyTorch, or scikit-learn.
- Knowledge of streaming data processing frameworks like Apache Kafka or Apache Beam.
- Familiarity with data visualization tools such as Tableau, Power BI, or matplotlib/seaborn.
