AI Engineer- Manager

Responsibilities

• Develop sophisticated generative AI solutions; provide technical guidance to a team of AI engineers and ensure alignment with microservice-based architecture and business requirements
• Collaborate closely with product managers, audit subject matter experts, and engineering teams to translate complex business requirements into scalable and reliable technical solutions
• Champion a culture of quality and innovation within engineering teams; identify opportunities to continually improve solutions
• Drive quality SDLC processes with AI engineering teams; deliver solutions on time to meet business cycle timelines
• Oversee the development of advanced context engineering strategies to manage diverse and sensitive client data; ensure solutions are versatile and effective across industries
• Mentor and develop junior engineers; foster technical excellence and professional growth while promoting best practices within the agile development process
• Act with integrity, professionalism, and personal responsibility to uphold KPMG's respectful and courteous work environment

Qualifications

• Minimum five years of recent experience in software engineering with a significant focus on building and deploying AI/ML models and systems in a production environment
• Master's degree from an accredited college or university in computer science, engineering, artificial intelligence, or a related technical field is preferred; minimum of a Bachelor's degree is required
• Practical expertise with LLMs (for example, Azure OpenAI, Google Cloud), AI frameworks (LangChain/LangGraph, Semantic Kernel), and building modern AI agent and orchestration patterns
• Proven experience designing and implementing RAG pipelines using technologies like Azure AI Search; strong understanding of data integration with platforms such as Databricks or Microsoft Fabric
• Proficiency with agile methodologies and SDLC tools including Azure DevOps, Git for version control, and implementing CI/CD pipelines for automated testing and deployment
• Excellent problem-solving skills; able to communicate complex technical concepts effectively to both technical and non-technical stakeholders