Manager, AI Engineer

About the role

KPMG Advisory is at the forefront of transformation, offering excellent opportunities for individuals to advance their careers and expertise. Our professionals thrive in a collaborative, team-driven culture where adaptability is key. At KPMG, our people are our top priority, with access to world-class training, leading market tools, and a wealth of learning and career development opportunities. This role is ideal for someone looking to deepen their experiences, advance their skills, and have a meaningful impact in a firm that values team connection and personal growth.

Responsibilities

• End-to-end design and development of AI/ML solutions, leveraging cloud AI services (Microsoft Azure, AWS, Google Cloud).
• Define solution architectures that integrate LLMs, generative AI, and traditional ML with enterprise platforms.
• Manage AI projects including architecture design, model development, integration, and testing, ensuring adherence to best practices in MLOps, security, compliance, and scalability for enterprise-grade adoption.
• Partner directly with clients to translate business objectives into technical solutions, aligning with enterprise strategy and measurable outcomes.
• Lead workshops and design sessions with executives, business stakeholders, and technical teams to shape AI roadmaps.
• Oversee deliverable quality and timelines, proactively managing risks and dependencies.
• Mentor and coach junior engineers and consultants, fostering a culture of innovation, technical excellence, and continuous learning.
• Collaborate with strategic alliance partners (Microsoft, Google, AWS, Salesforce) to incorporate the latest ecosystem innovations into client engagements.
• Stay current with emerging AI/ML technologies, frameworks, and tools, and evaluate their applicability for client needs.
• Act with integrity, professionalism, and personal responsibility to uphold KPMG's respectful and courteous work environment.

Requirements

• Minimum five years of recent professional experience in AI/ML, data engineering, or cloud solution engineering, with at least two years in a consulting or client-facing leadership role.
• Bachelor’s degree from an accredited college or university in computer science, data science, engineering, or a related field (Master’s degree preferred).
• Professional certifications in cloud AI/ML platforms (e.g., Azure AI Engineer Associate, AWS ML Specialty, Google Cloud ML Engineer) are a plus.
• Track record of delivering AI/ML solutions at enterprise scale, including integrations with core business systems.
• Demonstrated ability to lead technical teams, manage deliverables, and build trusted client relationships.
• Hands-on expertise with at least two major cloud AI platforms (Azure AI/ML, AWS Bedrock/SageMaker, or Google Cloud Vertex AI).
• Proficiency in Python (or other relevant languages) with strong experience in API development, microservices, containers, and CI/CD pipelines.
• Familiarity with MLOps frameworks (model monitoring, retraining pipelines, drift detection) and modern data engineering practices.
• Experience in building conversational AI/chatbots, generative AI use cases, or AI-powered automation solutions.
• Knowledge of AI security, data privacy, governance, and ethical AI frameworks.
• Strong problem-solving skills with the ability to translate complex technical concepts for executives.
• Excellent verbal and written communication skills, with experience creating client-facing deliverables.
• Willingness and ability to travel.
• Must be authorized to work in the U.S. without the need for employment-based visa sponsorship now or in the future.

Pay

California Salary Range: $153,710 – $267,030. Salary ranges for other locations can be found here. Any offered salary is determined based on relevant factors such as applicant's skills, job responsibilities, prior relevant experience, certain degrees and certifications, and market considerations.

Benefits

• Comprehensive medical, dental, and vision coverage.
• Disability and life insurance.
• 401(k) plans.
• Robust suite of personal well-being benefits to support mental health.
• Personal Time Off per fiscal year, based on job classification, standard work hours, and years of service.
• Two annual breaks where employees are not required to use Personal Time Off: one at year-end and another around the July 4th holiday.
• Paid holidays as per KPMG’s published calendar.

Additional details about benefits can be found on the KPMG US Careers site.