Manager, AI Engineer

About the role

KPMG Advisory practice is seeking a Manager, AI Engineer to join our Advisory Services practice. This role offers opportunities to advance your career and expertise in a collaborative, team-driven culture with access to world-class training facilities and leading market tools.

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, and ensure projects follow best practices in MLOps, security, compliance, and scalability to support 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, while 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

Qualifications

• Minimum five years of recent professional experience in AI/ML, data engineering, or cloud solution engineering, with a minimum two years in a consulting or client-facing leadership role
• Minimum of a Bachelor's degree from an accredited college or university in computer science, data science, engineering, or related field required; 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 (and/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
• Applicants must be authorized to work in the U.S. without the need for employment-based visa sponsorship now or in the future (no sponsorship available for H-1B, L-1, TN, O-1, E-3, H-1B1, F-1, J-1, OPT, CPT or any other employment-based visa)

Pay

California Salary Range: $153,710 - $267,030. 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 and dental plans, 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)
• Annual published calendar of holidays, plus two breaks each year where employees are not required to use Personal Time Off (year-end and around the July 4th holiday)