Associate Generative AI Engineer

Description:

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