Autofleet

AI Engineer

• Design, build, and deploy AI agents that automate and augment high-value workflows across business functions.
• Own the end-to-end agent stack, including tool use, memory management, multi-step planning, human-in-the-loop escalation patterns, guardrails, and audit trails.
• Define agent evaluation frameworks measuring task completion, accuracy, hallucination rates, latency, and business impact.
• Iterate on agent behavior using real usage data and stakeholder feedback.
• Implement integrations allowing agents to take automated actions on behalf of users.
• Collaborate with engineering teams to design, build, and maintain production pipelines.

Artificial Intelligence

• Design, build, and deploy AI agents that automate and augment high-value workflows across business functions.
• Own the end-to-end agent stack, including tool use, memory management, multi-step planning, human-in-the-loop escalation patterns, guardrails, and audit trails.
• Define agent evaluation frameworks measuring task completion, accuracy, hallucination rates, latency, and business impact.
• Iterate on agent behavior based on real usage data and stakeholder feedback.
• Collaborate with engineering teams to design, build, and maintain production pipelines.
• Stay current with developments in AI and machine learning, particularly large language models, and explore applications for improving products and services.

AI Applied Researcher

Product Manager

• Own a core product area end to end, working with a dedicated squad of engineers, setting direction, prioritising the backlog, and steering the squad from idea to production
• Contribute to every stage of the product life cycle, including roadmap planning, defining needs, writing PRDs, collaborating with R&D, and managing production releases
• Meet with clients to align product goals with their needs
• Conduct industry research, define problems and needs, and discover new opportunities
• Build wireframes and collaborate with designers to ensure usability, requirements compliance, and visual quality
• Manage QA and feature release processes
• Monitor adoption of new functionality and measure performance against defined KPIs
• Communicate project status, issues, and risks to the squad and wider business team
• Maintain close contact with clients to deliver value, enhance products, and learn from client experience

Data Engineer

• Design, implement, and maintain robust, scalable data pipelines for batch and real-time processing using Spark and other modern tools
• Own backend data infrastructure, including ingestion, transformation, validation, and orchestration of large-scale datasets
• Leverage Google Cloud Platform services to architect and operate scalable, secure, and cost-effective data solutions
• Develop and optimize ETL/ELT workflows across multiple environments for internal applications, analytics, and machine learning workflows
• Build and maintain data marts and data models focused on performance, data quality, and long-term maintainability
• Collaborate with development teams, product managers, and external stakeholders to translate data requirements into scalable solutions
• Help drive architectural decisions around distributed data processing, pipeline reliability, and scalability

AI Engineer

AI Applied Researcher

Product Manager

Senior Data Engineer