AI Solution Development Manager

Assistant Manager

Key Responsibilities:

1. AI Solution Development:
   • Contribute to the design, development, and implementation of generative AI models to address client business challenges.
   • Collaborate with senior AI engineers and data scientists to build AI solutions that align with business goals.
   • Participate in the creation of Proof of Concepts (PoCs), Minimal Viable Products (MVPs), and fully developed AI projects that drive business impact.
2. Client Project Delivery & Team Management:
   • Support the delivery of AI solutions for client projects, ensuring successful outcomes and timely execution.
   • Manage and mentor a team of AI engineers and data scientists, providing guidance and support throughout the project lifecycle.
   • Collaborate with cross-functional teams to gather client requirements, translate them into technical solutions, and ensure seamless implementation of AI models.
3. Coding & Implementation:
   • Develop and optimize generative AI models, ensuring high-quality code that meets production standards.
   • Work with tools like TensorFlow, PyTorch, Databricks, and Snowflake to implement and deploy AI models in cloud environments.
   • Ensure the integration of AI models into existing systems, managing version control and collaborating on continuous integration/continuous delivery (CI/CD) processes.
4. Data Management & Integration:
   • Work closely with data engineering teams to ensure smooth data flow, integration, and management for AI model development.
   • Ensure AI models are well-integrated into existing data pipelines, with an emphasis on data quality and consistency.
   • Adhere to best practices for data governance, security, and privacy, particularly in relation to sensitive client data.
5. Business Development & Practice Building:
   • Assist in identifying opportunities for AI solutions that meet client needs, supporting feasibility studies and the development of tailored data strategies.
   • Contribute to business development efforts by supporting RFP responses, proposals, and client demos, highlighting the value of AI-driven solutions.
   • Help expand KPMG's AI practice by bringing innovative ideas and solutions to clients and assisting in the growth of AI capabilities.
6. Data Governance & Security:
   • Ensure AI models and data processing are compliant with KPMG’s data governance policies and industry regulations.
   • Implement best practices in data privacy, security, and ethical AI, particularly when working with sensitive or regulated data.
   • Contribute to the development of guidelines and frameworks for the secure handling of data in AI projects.

Key Responsibilities:

1. AI Solution Development:
   • Contribute to the design, development, and implementation of generative AI models to address client business challenges.
   • Collaborate with senior AI engineers and data scientists to build AI solutions that align with business goals.
   • Participate in the creation of Proof of Concepts (PoCs), Minimal Viable Products (MVPs), and fully developed AI projects that drive business impact.
2. Client Project Delivery & Team Management:
   • Support the delivery of AI solutions for client projects, ensuring successful outcomes and timely execution.
   • Manage and mentor a team of AI engineers and data scientists, providing guidance and support throughout the project lifecycle.
   • Collaborate with cross-functional teams to gather client requirements, translate them into technical solutions, and ensure seamless implementation of AI models.
3. Coding & Implementation:
   • Develop and optimize generative AI models, ensuring high-quality code that meets production standards.
   • Work with tools like TensorFlow, PyTorch, Databricks, and Snowflake to implement and deploy AI models in cloud environments.
   • Ensure the integration of AI models into existing systems, managing version control and collaborating on continuous integration/continuous delivery (CI/CD) processes.
4. Data Management & Integration:
   • Work closely with data engineering teams to ensure smooth data flow, integration, and management for AI model development.
   • Ensure AI models are well-integrated into existing data pipelines, with an emphasis on data quality and consistency.
   • Adhere to best practices for data governance, security, and privacy, particularly in relation to sensitive client data.
5. Business Development & Practice Building:
   • Assist in identifying opportunities for AI solutions that meet client needs, supporting feasibility studies and the development of tailored data strategies.
   • Contribute to business development efforts by supporting RFP responses, proposals, and client demos, highlighting the value of AI-driven solutions.
   • Help expand KPMG's AI practice by bringing innovative ideas and solutions to clients and assisting in the growth of AI capabilities.
6. Data Governance & Security:
   • Ensure AI models and data processing are compliant with KPMG’s data governance policies and industry regulations.
   • Implement best practices in data privacy, security, and ethical AI, particularly when working with sensitive or regulated data.
   • Contribute to the development of guidelines and frameworks for the secure handling of data in AI projects.

Qualifications & Experience:

• Educational Background:
  • BSc in Computer Science, Engineering, Statistics, or a related field.
  • Advanced certifications or coursework in AI/ML or data engineering are a plus.

(Additionally, if you feel you are the right fit for the listed skills and can demonstrate why you would be a good fit for the role, we are open to all backgrounds that have demonstrated commitment and progression of your skillset through personal and professional engagements. We want to continue to build out our team with the best and brightest minds in the industry, and if you feel you can contribute to our strategic goals and our clients, we would love to hear from you)

• Work Experience:
  • 5+ years of experience in AI/ML, with a focus on developing and deploying generative AI solutions.
  • Proven experience working with Large Language Models (LLMs) like GPT, BERT, or similar technologies.
  • Strong expertise in AI frameworks such as TensorFlow, PyTorch, and cloud platforms like Databricks and Snowflake.

 

 

• Skills:
  • Proficient in designing and coding generative AI models, including prompt engineering for LLMs like GPT and BERT.
  • Strong understanding of AI/ML algorithms, model optimization, and deployment in scalable cloud environments.
  • Experience with version control (e.g., Git), Docker, and data engineering tools such as Hadoop, Spark, and Elasticsearch.
  • Excellent team collaboration, leadership, and communication skills, with the ability to manage and mentor junior team members.

Experience Level

Mid Level