AI Systems Engineer

Job description

Unleash AI Innovators, Securely Software is being rewritten in real time. AI agents are starting to write more code than humans do, at a speed no security team has ever had to match, and that single shift is opening up the biggest opportunity our industry has seen in a decade. We're not bracing for it, we're building the company that owns it. Snyk is building the next generation security platform where security isn't a set of tools people operate. It's a team of security agents working alongside your engineers, finding, fixing, and governing risk at the speed software is now built. These agents work alongside both the company build and the agents they adopt. Security stops being a queue of work waiting for people, and becomes a coordinated workforce companies direct and trust. Snyk is the leader in secure AI software development, helping millions of developers develop fast and stay secure as AI transforms how software is built. Our AI-native Developer Security Platform integrates seamlessly into development and security workflows, making it easy to find, fix, and prevent vulnerabilities — from code and dependencies to containers and cloud. Our mission is to empower every developer to innovate securely in the AI era — boosting productivity while reducing business risk. We’re not your average security company - we build Snyk on One Team, Care Deeply, Customer Centric, and Forward Thinking. It’s how we stay driven, supportive, and always one step ahead as AI reshapes our world. Our Opportunity We're seeking a talented and results-oriented AI Systems Engineer to join our growing team! You'll be instrumental in designing, developing, and deploying innovative AI solutions that empower our internal operations and drive business value. You’ll Spend Your Time: Building and maintaining internal AI systems: Develop and maintain software pipelines for training, deploying, and monitoring machine learning and Gen. AI projects used for various internal tasks (e.g., knowledge management, data analysis, process automation, decision support). Optimizing AI infrastructure: Collaborate on optimizing our AI infrastructure for scalability, efficiency, and cost-effectiveness. Performing data integration and engineering: Ensure seamless data flow for AI projects by integrating data from various sources and performing necessary cleaning and transformation. Collaborating with intern…