AI Engineer
At a glance
Mid-level AI Engineering role at Autofleet. Tel Aviv-Yafo.
Pay not stated AI Engineer salary
aimlroles summary, based on the employer's posting.
What you'll do
- Build and launch AI agents that take on valuable workflows across different business functions
- Shape the agent system end to end, including tool use, memory, planning, safeguards and human review
- Create ways to assess task success, accuracy, hallucinations, speed and business value, then improve agents using usage data and feedback
- Connect agents to systems so they can act for users, and maintain production pipelines with engineering teams
What you bring
- A bachelor's degree in a quantitative discipline such as computer science, engineering or mathematics
- At least five years building software systems for production, beyond research, experiments or prompt writing
- Practical experience running AI or LLM systems in production, preferably with agent workflows, tool calls or evaluations
- Strong backend skills with Python, distributed systems and cloud-based architecture
Who this fits
This suits a mid-level AI engineer with production software and AI systems experience who wants to build and improve agent workflows. The role is onsite in Tel Aviv-Yafo, Israel.
From the employer
We are making the future of Mobility come to life starting today.
At Autofleet we support the world's largest vehicle fleet operators and transportation providers to optimize existing operations and seamlessly launch new, dynamic business models - driving efficient operations and maximizing utilization.
We are looking for a talented AI Engineer to help us develop advanced AI solutions that will empower impactful projects. The Data Science team leads the AI research and innovation efforts of the company, and is focused on pushing AI boundaries to enhance the product and optimize processes.
What You’ll Do
- Enterprise AI Agent Development: Designing, building, and deploying AI agents that automate and augment high-value workflows across business functions
- Agentic Architecture & Orchestration: Owning the end-to-end agent stack - from tool use, memory management, and multi-step planning to human-in-the-loop escalation patterns, guardrails and audit trails.
- Evaluation & Continuous Improvement: Defining agent evaluation frameworks that measure task completion, accuracy, hallucination rates, latency, and business impact - then iterating on agent behavior based on real usage data and stakeholder feedback.
- Implement integrations that allow agents to take automated actions on behalf of users, streamlining workflows and reducing overhead.
- Collaborate with engineering teams to design, build, and maintain production pipelines.
Requirements
- Bachelor’s degree in Computer Science, Engineering, Mathematics, Physics, or a related quantitative discipline.
- 5+ years of software engineering experience, with proven ability to build production-grade systems beyond research, experimentation, or prompt engineering.
- Hands-on experience building and operating production-grade AI/LLM systems, ideally including agentic workflows, tool-calling, orchestration, evaluations, or multi-step reasoning systems.
- Strong backend expertise, including Python, distributed systems, and cloud-native architecture.
- Familiarity with the AI Agents ecosystem, including different LLM providers, vector store solutions, MCPs, A2A and more.
- Familiarity with REST APIs and integrating external data sources.