Staff / Senior Staff Engineer, AI Products

Mission

We build security systems that can make good decisions from incomplete and noisy information. Modern security products rarely get a perfect signal. They have to combine behavioral patterns, historical context, content, infrastructure signals, and other telemetry to determine whether something is actually risky—and decide what to do about it. You’ll work on problems like:

• Turning large volumes of noisy security data into high-confidence detections.
• Influencing/Participating in model creation to build the best product.
• Understanding what “normal” looks like when it is different for every user and organization.
• Moving new detection ideas from prototype to reliable production systems.
• Making sure the systems we build are actually correct.

Your Mission

The systems you build will operate in environments where false positives have consequences and latency, precision, reliability, and customer trust all matter. You’ll work across detection systems, distributed infrastructure, product surfaces, and AI inference—and you’ll be expected to understand the full path from raw data to a customer-visible decision.

Growth Opportunity

We want someone who is outgrowing their current scope. Maybe you’re a Staff engineer and the path to meaningful leadership at your company is measured in years. Maybe you’re a Senior Staff engineer who wants to do more than influence architecture from the side. Maybe you recently became a manager and discovered you don’t want to choose between being deeply technical and building an organization. Or maybe you’re already managing engineers, but your company isn’t moving fast enough and you want to get closer to the problems again. At Aegis, the opportunity is to start as a senior technical owner and grow with the product. At the beginning: you’ll be deeply hands-on—shipping code, understanding the systems, setting technical direction, and establishing credibility through execution. As you prove the scope: you’ll increasingly lead projects and engineers, own a larger part of the technical roadmap, participate in hiring, and become responsible for how the team operates. As the company grows: the role can expand into formal engineering leadership, with ownership of people, roadmap, hiring, and strategy.

Why Aegis

You’ll work on problems at the intersection of AI and security. AI isn’t an add-on to the product; reasoning, learning, and adaptation are core to how we think about detection. You’ll build systems that make real decisions. This is production security engineering, where quality can be measured and the consequences matter. You’ll have unusual ownership. Small teams mean you can influence architecture, product direction, and customer experience instead of owning one narrow layer. You’ll work with people who have built defensive systems at massive scale. The team brings deep experience in security, distributed systems, and applied AI. You’ll move quickly. We value engineers who can go from an ambiguous problem to a working system without waiting for a large process to form around them.

What We’re Looking For

We care less about whether your previous title perfectly matches this one and more about the scope you’ve already demonstrated. You: Have operated at Staff-level technical scope, or have equivalent experience leading technically complex systems and teams. Have built production systems where false positives, correctness, reliability, or risk mattered. Can move between architecture and implementation without treating either as someone else’s job. Are comfortable making decisions with incomplete information and updating them quickly as you learn. Can prioritize across multiple important problems instead of treating every request as equally urgent. Communicate technical decisions clearly in writing. Make other engineers more effective, whether or not you have formally managed them. Want significantly more responsibility than your current environment can give you. Most importantly, you are excited by the problems themselves. The leadership opportunity is real, but the path to it starts with being an exceptional engineer.

Bonus Experience

• Security detection, fraud, abuse, or other adversarial systems
• Behavioral or anomaly detection
• Data-intensive distributed systems
• LLMs used in production decision-making
• Building evaluation systems and labeled datasets for ML or AI products
• Enterprise security products or integrations
• Taking an early product from a small number of users to broad production adoption
• Building or leading engineering teams in an early-stage company