Full Stack Developer : Agentic AI
22 days ago Haifa, Israel
About us
Working at Apple means doing more than you ever thought possible and having more impact than you ever imagined.
- Size: 10,000+ employees
- Industry: Technology
As a member of our ML group, you will design and build agentic GenAI systems used by chip design engineers to accelerate their day-to-day workflows. We are looking for a software engineer with strong backend skills, a product mindset, and the curiosity to bring LLM-powered agents into the toolchains and Linux environments where chips are actually designed. Success in this role means owning the agentic infrastructure end-to-end: from the platform our agents run on, to the integrations that let them safely act inside our customers' existing flows.
Description
You will join a growing team of ML and software engineers building GenAI solutions for chip design teams. In this role, you will:
* Architect, build, and operate the agentic infrastructure our team relies on:including LLM orchestration, tool-calling layers, multi-agent workflows, and the services that host them.
* Design and implement software solutions for chip design engineers, translating their workflows into reliable, automated agent-driven systems.
* Integrate our agents and services with existing Linux-based environments, in-house tools developed by the team, and third-party EDA tools.
* Manage agentic and ML workflows in production to ensure performance, high availability, and resource efficiency.
* Deploy and maintain production services, with proactive monitoring to catch quality and infrastructure regressions before they reach users.
* Build automated evaluation frameworks to measure retrieval quality, agent execution, and LLM output accuracy across releases.
* Partner with CAD teams to integrate pipelines and agents into CI/CD, ensuring reliable deployments and safe rollbacks.
* Implement access controls, authentication, and secret-handling practices appropriate for working with sensitive design data.
* Collaborate closely with ML engineers, researchers, and our customer teams.
Preferred Qualifications
Experience implementing observability practices and performance benchmarking pipelines to ensure AI system reliability.
Familiarity with chip design or EDA environments.
Experience with cloud platforms (e.g., AWS, GCP, or Azure)
Prior experience in a fast-paced startup or agile product development environment.
BSc or MSc in Computer Science, Computer Engineering, Electrical Engineering, or related fields.
Minimum Qualifications
5+ years of full stack development experience, working with relational and NoSQL databases (e.g., MongoDB, SQL).
Strong object-oriented programming and system design skills, with proficiency in both TypeScript and Python across frontend and backend development.
Hands-on experience building dynamic web applications utilizing React for the frontend and Node.js or Python for the backend.
Familiarity with microservices, containerization (Docker), orchestration (e.g., Kubernetes), and CI/CD practices (e.g., GitLab, GitHub Actions, Jenkins).
Proven experience designing, developing, and scaling real-time and distributed systems.
Hands-on experience deploying LLM-powered applications, agents, or related components (e.g., vector databases, RAG pipelines) in production.
Excellent communication and collaboration skills, with the ability to bridge engineering teams and explain technical trade-offs clearly.
Description
You will join a growing team of ML and software engineers building GenAI solutions for chip design teams. In this role, you will:
* Architect, build, and operate the agentic infrastructure our team relies on:including LLM orchestration, tool-calling layers, multi-agent workflows, and the services that host them.
* Design and implement software solutions for chip design engineers, translating their workflows into reliable, automated agent-driven systems.
* Integrate our agents and services with existing Linux-based environments, in-house tools developed by the team, and third-party EDA tools.
* Manage agentic and ML workflows in production to ensure performance, high availability, and resource efficiency.
* Deploy and maintain production services, with proactive monitoring to catch quality and infrastructure regressions before they reach users.
* Build automated evaluation frameworks to measure retrieval quality, agent execution, and LLM output accuracy across releases.
* Partner with CAD teams to integrate pipelines and agents into CI/CD, ensuring reliable deployments and safe rollbacks.
* Implement access controls, authentication, and secret-handling practices appropriate for working with sensitive design data.
* Collaborate closely with ML engineers, researchers, and our customer teams.
Preferred Qualifications
Experience implementing observability practices and performance benchmarking pipelines to ensure AI system reliability.
Familiarity with chip design or EDA environments.
Experience with cloud platforms (e.g., AWS, GCP, or Azure)
Prior experience in a fast-paced startup or agile product development environment.
BSc or MSc in Computer Science, Computer Engineering, Electrical Engineering, or related fields.
Minimum Qualifications
5+ years of full stack development experience, working with relational and NoSQL databases (e.g., MongoDB, SQL).
Strong object-oriented programming and system design skills, with proficiency in both TypeScript and Python across frontend and backend development.
Hands-on experience building dynamic web applications utilizing React for the frontend and Node.js or Python for the backend.
Familiarity with microservices, containerization (Docker), orchestration (e.g., Kubernetes), and CI/CD practices (e.g., GitLab, GitHub Actions, Jenkins).
Proven experience designing, developing, and scaling real-time and distributed systems.
Hands-on experience deploying LLM-powered applications, agents, or related components (e.g., vector databases, RAG pipelines) in production.
Excellent communication and collaboration skills, with the ability to bridge engineering teams and explain technical trade-offs clearly.
Additional Information
- Posted: 22 days ago