Site Reliability Engineer | AI Infrastructure

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Site Reliability Engineer AI Infrastructure TLV

Location: Tel Aviv Israel (Hybrid 3 days in-office)

Reports to: Head of AI Solutions and Innovations JLL Technologies

About Us

JLL (NYSE: JLL) is a Fortune 500 commercial real estate company. JLL Technologies is its tech arm. The Tel Aviv office runs AI data science and ML work that feeds directly into how the business operates. Our teams build and run production AI systems used in decision-making across the company.

The Role

Were hiring for a new AI Engineering team in Tel Aviv and you would be the first infrastructure hire. You will own the platform layer for AI agents the team builds: deployment architecture observability and production reliability.

The teams first two projects: an agent that automates internal governance processes (vendor reviews security questionnaires tool provisioning) and an agent that helps engineering teams prepare for architecture reviews. Both integrate with external APIs (LLM providers OneTrust ServiceNow) handle structured decision logic and manage sensitive data flows with audit requirements.

Highlights

- Greenfield but with real constraints. Youre building on Azure/AWS with enterprise security requirements. The challenge is designing deployment and observability for LLM-backed services. You need to track output quality cost per invocation and model drift.

- Enterprise complexity startup autonomy. Ownership and greenfield environment of a startup with the integration challenges of a Fortune 200: connecting AI services to real enterprise systems.

- More than infrastructure. Your core is SRE but youll also write agent code in TypeScript and Python work with data pipelines and ship features alongside the team.

What the Work Looks Like

AI Service Infrastructure - Design and maintain deployment and release infrastructure for AI agents. The stack is cloud-native (Azure/AWS) with services that call LLM APIs connect to enterprise systems and handle structured data.

Observability & Reliability - Build monitoring and observability for AI services. Ensure model response quality doesnt degrade silently by tracking errors logging cost spikes and monitoring upstream API changes.

Security & Compliance - These agents handle sensitive workflows with elevated security requirements. You will work with JLLs security team on standards but you own how theyre implemented in the infrastructure.

Developer Experience - Create tooling that makes it easy for the team to build test and deploy. The patterns you set become the teams defaults.

What Were Looking For

Required:

- 5 years in SRE platform engineering DevOps or infrastructure roles with experience owning infrastructure end-to-end

- Strong experience with cloud platforms (Azure or AWS) containerization (Docker Kubernetes) and CI/CD pipelines

- Infrastructure-as-code experience (Terraform CDK or CloudFormation)

- Monitoring and observability (Datadog Splunk CloudWatch or similar)

- Infrastructure fundamentals: Linux networking security

- Incident management experience: on-call production incidents post-mortems

- Comfortable working independently with broad ownership and high accountability

- Strong written and verbal English for async collaboration with distributed teams

Preferred:

- Experience with AI/ML infrastructure: model serving LLM API integration vector databases or evaluation pipelines

- Comfortable writing production code in TypeScript or Python not just scripts

- Experience building self-service developer tooling or internal platforms

- Cost optimization for cloud and API-based workloads

- Security engineering experience especially in enterprise or compliance-heavy environments

Working Here

- Hybrid: 3 days in-office. 30 engineers and data scientists in the TLV office.

- Team: Distributed across Israel Czechia the US India and Singapore.

- Language: The team operates in English. Hebrew is the office language but not required for the role.

Compensation and Process

Base salary RSUs (JLL is NYSE-listed standard 4-year vest) keren hishtalmut and annual bonus. We share range details early in the process.

Process: Initial conversation with the hiring manager technical deep-dive (system design live troubleshooting no leetcode) team conversation. Typically 2-3 weeks end to end.

Location:

If this job description resonates with you we encourage you to apply even if you dont meet all of the requirements. Were interested in getting to know you and what you bring to the table!

At JLL we harness the power of artificial intelligence (AI) to efficiently accelerate meaningful connections between candidates and opportunities. Using AI capabilities we analyze your application for relevant skills experiences and qualifications to generate valuable insights about how your unique profile aligns with the specific requirements of the role yourepursuing.

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