About Kandji
Kandji is the Apple device management and security platform that empowers secure and productive global work. With Kandji, Apple devices transform themselves into enterprise-ready endpoints, with all the right apps, settings, and security systems in place. Through advanced automation and thoughtful experiences, we’re bringing much-needed harmony to the way IT, InfoSec, and Apple device users work today and tomorrow.
Some of the smartest money in tech has partnered with Kandji to realize our vision, including Tiger Global, Felicis, Greycroft, First Round Capital, and Okta Ventures. In July 2024, Kandji raised $100 million in capital from General Catalyst, bringing Kandji’s valuation to $850 Million.
Since Kandji’s Series C in 2021, the company has seen a 600%+ increase in annual recurring revenue, and its customer base has grown nearly 4X across 40+ industries. Notable customers include Allbirds, Canva, and Notion, and the company has partnerships with such industry giants as ServiceNow, AWS, and Okta.
Kandji was also named to Forbes’ Next Billion Dollar Startup List 2023 and recognized as a top venture-backed startup with the potential to reach unicorn status.
The Opportunity
We are seeking a highly skilled and experienced Staff AI Engineer to join our Kandji Platform Engineering team. In this role, you will play a critical part in both building the core AI platform and directly applying large language models (LLMs) to deliver intelligent features across Kandji. You will focus on backend systems that enable scalable, reliable, and secure AI-powered capabilities, while also working hands-on with LLMs to solve real user problems and drive product innovation.
In this role, youʼll focus on creating reusable infrastructure, frameworks, and services that enable data scientists and software engineers to rapidly experiment, deploy, and monitor AI at scale.
Youʼll collaborate across engineering, product, and research teams to ensure Kandjiʼs AI offering is secure, reliable, and optimized for performance, while enabling innovation and experimentation.
How You'll Make a Difference Day to Day:
Architect, design, and implement scalable AI platform services and components that enable the development of intelligent agents and LLM-powered applications, while supporting the deployment and orchestration of LLMs and other AI models.Apply LLMs and other AI technologies directly to build and enhance Kandjiʼs intelligent features, working closely with product and engineering teams to deliver impactful solutions.Build LLM-powered agents that autonomously reason through complex workflows.Develop full-stack product surfaces (backend & frontend) that incorporate AI into user experiences.Familiarity with the AI development stack (RAG, vector databases, LLM observability, eval pipelines).Partner with Product Engineering teams to design ML-driven features that automate IT security workflows.Implement scalable APIs and microservices that expose AI models and services to product teams.Collaborate with our core services infrastructure team to support the execution, monitoring, logging, and automated evaluation of AI agents, ensuring high reliability and performance of AI services in production environments. Work closely with the Data Science team responsible for building LLMs / agents.Integrate with multiple LLM providers (e.g., OpenAI, Anthropic, xAI, Google) and manage model selection, routing, and fallback strategies for optimal performance and cost.Drive the adoption of best practices in AI privacy, security, and compliance, including secure data handling, and regulatory adherence.Optimize platform performance, scalability, and cost-efficiency, leveraging cloud-native technologies and distributed systems.Stay current with advancements in AI infrastructure, agent-focused MLOps, and LLM applications, and apply relevant innovations to enhance Kandjiʼs AI platform.Collaborate cross-functionally with product, frontend, and data teams to deliver seamless, reliable, and user-centric AI experiences.
We’d love to hear from you if you have
Bachelorʼs or Masterʼs degree in Computer Science, Machine Learning, Data Science, or related field.Extensive experience designing and building scalable AI/ML platforms or infrastructure in a production environment.Proven track record of applying LLMs and AI models to real-world product features and user-facing solutions, with a strong understanding of their operational requirements. Deep expertise in backend engineering, distributed systems, and cloud-native technologies (e.g., Kubernetes, Docker, AWS/GCP).Proficiency in agentic and orchestration frameworks (e.g., Langchain, CrewAI, pydantic-ai, LangGraph, Airflow, Kubeflow, Ray, or similar).Strong programming skills in Python, Go, TypeScript or similar languages used for backend and AI platform development, and experience with ML frameworks (TensorFlow, PyTorch, scikit-learn).Experience with MLOps best practices, including model deployment, monitoring, logging, and automated evaluation. Knowledge of MLOps tools (MLflow, Kubeflow) and practices.Demonstrated ability to address AI privacy and security challenges, as well as compliance with data protection regulations.Familiarity with RAG and its integration into AI-driven applications.Excellent collaboration and communication skills, with a track record of working effectively in cross-functional teams.Passion for staying at the forefront of AI infrastructure and applying new technologies to solve real-world problems at scale.
