AI Backend Engineer

Reposted 7 Days Ago
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תל אביב
In-Office
Junior
Fintech • Payments • Professional Services • Financial Services
The Role
Design, build, deploy, and maintain backend systems integrating Generative AI. Implement APIs, databases, authentication, multi-agent orchestration with LLMs, optimize performance and cost, deploy on cloud (GCP/Azure/AWS), and collaborate with clients and DevOps on delivery.
Summary Generated by Built In
Description

We Are KPMG Israel.

KPMG Israel is more than a professional services firm, we are a community of people driven by impact.

As part of a leading global network, we partner with the most influential organizations to drive large-scale business and technology transformation, combining strategic thinking, innovation, and advanced technologies.

Guided by integrity, excellence, and forward thinking, we help organizations navigate complexity and create real change. 

Our people are at the center, with space to lead, experiment, and grow in a dynamic and collaborative environment that connects personal development with meaningful impact on the future of business and society.

About the Role

We're looking for a AI Backend Engineer with a data science foundation to join our AI team and build production systems that integrate Generative AI capabilities. You'll design and implement end-to-end solutions APIs, databases, orchestration, and cloud infrastructure for clients across a wide range of sectors.

This role is ideal for someone who thinks in systems, enjoys working with GenAI technologies, and wants to grow into designing complex architectures. You'll work alongside senior engineers on real delivery projects from day one.

Key Responsibilities

· Design and build backend systems APIs, databases, authentication, and integrations

· Implement multi-agent architectures and orchestration workflows combining LLMs with backend logic

· Deploy and maintain systems on GCP, Azure, or AWS

· Optimize AI system performance, cost, and reliability

· Collaborate with client teams, DevOps, and stakeholders on project delivery

· Contribute to technical discussions and solution design

Requirements

Must Have

· 1+ years of software development experience

· Strong proficiency in Python for backend development

· Experience building backend systems (APIs, databases, or services)

· Solid understanding of data science fundamentals statistics, ML concepts, and working with data pipelines

· Familiarity with at least one major cloud platform (GCP, Azure, or AWS)

· Understanding of software engineering principles and architecture basics

· Familiarity with GenAI / LLM concepts

· Bachelor's degree in Computer Science, Data Science, or related field or equivalent practical experience

Advantages

· Experience with LLM provider APIs (OpenAI, Anthropic, Google)

· Exposure to multi-agent systems or LLM-based workflows

· Hands-on experience with ML frameworks (e.g., scikit-learn, PyTorch, TensorFlow)

· Academic research or projects in AI, NLP, or data science

· Personal or university projects involving multi-agent systems or ML model development

· Docker and Kubernetes experience

· Experience working on production systems in a client-facing environment

What We Offer

· Hands-on work designing end-to-end AI systems across multiple industries

· Exposure to diverse cloud platforms and technical challenges

· Mentorship and a clear path to grow into system design and technical leadership

· Continuous learning in a rapidly evolving field

Skills Required

  • 1+ years of software development experience
  • Strong proficiency in Python for backend development
  • Experience building backend systems (APIs, databases, or services)
  • Solid understanding of data science fundamentals, statistics, ML concepts, and working with data pipelines
  • Familiarity with at least one major cloud platform (GCP, Azure, or AWS)
  • Understanding of software engineering principles and architecture basics
  • Familiarity with GenAI / LLM concepts
  • Bachelor's degree in Computer Science, Data Science, or related field or equivalent practical experience
  • Experience with LLM provider APIs (OpenAI, Anthropic, Google)
  • Exposure to multi-agent systems or LLM-based workflows
  • Hands-on experience with ML frameworks (scikit-learn, PyTorch, TensorFlow)
  • Academic research or projects in AI, NLP, or data science
  • Personal or university projects involving multi-agent systems or ML model development
  • Docker and Kubernetes experience
  • Experience working on production systems in a client-facing environment

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.

  • Leave & Time Off Breadth Feedback suggests the firm provides generous Paid Time Off, paid holidays, sabbatical leave, military leave, paid volunteer time, and paid sick days. Flexibility is further supported through a hybrid work approach intended to promote well-being.
  • Healthcare Strength Feedback suggests employees have access to comprehensive health, dental, and vision insurance alongside mental health benefits. Tax-advantaged accounts such as FSA and HSA further strengthen the healthcare offering.
  • Retirement Support Feedback suggests the package includes a 401(k) plan, a pension plan, life and AD&D insurance, disability coverage, and retiree health and medical benefits. These elements indicate a strong focus on long-term financial security.

KPMG Insights

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The Company
HQ: New York, NY
231,171 Employees

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

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