At KPMG Israel, our Generative AI delivery team leads the market in advanced AI solution delivery. We work across the full spectrum of generative AI technologies, from large language models and multimodal architectures to autonomous agent systems and production-scale machine learning platforms.
Our work combines advanced engineering with strategic advisory capabilities, delivering AI-driven solutions that create measurable business value for clients.
We are seeking an Associate Generative AI Engineer to join our AI squad at KPMG. This role blends hands-on engineering with exposure to system design and client-facing delivery, making it an excellent opportunity for engineers early in their career to work on real, production-grade GenAI systems.
You will design, build, and operate LLM-based and agentic systems as part of cross-functional teams, contributing to both greenfield initiatives and the evolution of existing GenAI platforms. You will develop strong foundations in system architecture, backend engineering, and cloud-based GenAI delivery while working closely with more experienced engineers.
Key Responsibilities
GenAI Development & Implementation
• Develop end-to-end GenAI solutions from POC through production deployment
• Implement backend microservices and GenAI components using Python
• Contribute to the development of multi-agent systems, orchestration layers, and autonomous workflows
• Integrate and optimize LLMs and GenAI APIs within larger systems
• Participate in evaluating and improving system performance, scalability, reliability, and cost efficiency
Client Engagement & Collaboration
• Participate in technical discussions with clients and contribute to solution design discussions
• Support presentations, demos, and technical explanations for client stakeholders
• Collaborate closely with project managers, full-stack developers, and automation teams to deliver end-to-end solutions
Cloud & Platform Work
• Deploy and operate GenAI systems on GCP, Azure, and/or AWS
• Work with cloud-native AI services and managed platforms
• Contribute to monitoring, reliability, and operational stability of production environments
Continuous Learning & Practice Development
• Explore and evaluate emerging GenAI models, frameworks, and techniques
• Contribute to team best practices, internal documentation, and shared methodologies
• Continuously improve technical skills in LLM systems, agentic architectures, and cloud engineering
Technical Expertise
• Strong proficiency in Python for backend development and AI-related systems
• Solid understanding of large language models and generative AI techniques
• Experience contributing to agent-based workflows or orchestration logic
• Practical experience with prompt design and prompt optimization techniques
• Understanding of microservices architecture and API-based system design
• Hands-on experience with at least one major cloud platform (GCP, Azure, or AWS)
Professional Experience
• Up to 2 years of experience in software engineering, AI, or ML-related roles
• Experience contributing to production or production-adjacent systems
• Exposure to client-facing or consulting-style project delivery is an advantage
Education & Background
• Bachelor’s degree in Computer Science, AI, Machine Learning, or related technical field
(or equivalent practical experience and portfolio)
Soft Skills
• Strong analytical and problem-solving abilities
• Clear technical communication skills
• Ability to collaborate effectively across teams
• Adaptability and eagerness to learn in fast-paced environments
• Consulting mindset and client-oriented approach
What We Offer
• Opportunity to work on cutting-edge GenAI projects across diverse industries
• Hands-on involvement in LLM-based and agentic systems used in production
• Exposure to cloud-native AI platforms and modern system architectures
• Collaborative consulting environment with experienced engineers and advisors
• Continuous professional development in a rapidly evolving field
KPMG Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about KPMG and has not been reviewed or approved by KPMG.
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Leave & Time Off Breadth — Paid time off starts early in tenure and is supplemented by additional holiday weeks and a variety of paid leaves. Feedback suggests companywide breaks and multiple leave types provide meaningful downtime.
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Retirement Support — Retirement offerings include a firm-funded 401(k), company-paid retirement benefit, and pension options with vesting. Feedback suggests automatic contributions enhance long-term savings certainty.
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Healthcare Strength — Health coverage includes medical, dental, vision, disability, critical illness, and access to an EAP alongside FSAs/HSAs. Feedback suggests the breadth of health and wellness options is a strong component of total rewards.
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What We Do
KPMG is a global network of professional firms providing Audit, Tax and Advisory services. We have 273,000 outstanding professionals working together to deliver value in 143 countries and territories. With a worldwide presence, KPMG continues to build on our successes thanks to clear vision, defined values and, above all, our people. Our industry focus helps KPMG firms’ professionals develop a rich understanding of clients' businesses and the insight, skills and resources required to address industry-specific issues and opportunities. The independent member firms of the KPMG network are affiliated with KPMG International Cooperative (“KPMG International”), a Swiss entity. Each KPMG firm is a legally distinct and separate entity and describes itself as such
