At Supermodular AI, we help enterprises navigate AI Transformation. We believe in strategy through execution.
Most organizations understand the potential of AI, but struggle to translate that ambition into real operational change. The challenge is rarely the technology itself. It is how AI fits into complex systems, workflows, and engineering organizations that have evolved over years. We believe AI transformation cannot be designed purely in strategy documents. The real strategy only emerges by building, deploying, and operating AI systems inside the organization.
That’s why we work directly with enterprise IT and software teams to design and implement AI systems in real environments. This includes enabling engineering organizations to work in fundamentally new ways by introducing AI-native development practices, frameworks, and technical assets that change how teams build and operate software. It also includes building custom AI systems that unblock difficult modernization or harmonization efforts where traditional approaches have stalled.
Our team has a strong track record of building high-impact AI systems and scaling engineering teams inside complex enterprises. If you enjoy solving hard enterprise problems and turning ambitious ideas into systems that actually run in production, you’ll feel at home at supermodular.ai.
As a Forward Deployed Security Engineer (AI Systems) at Supermodular AI, you will work directly with enterprise IT and software teams to ensure AI systems operate securely, reliably, and safely in production environments.
You will be embedded in real enterprise environments, working alongside engineers and technical leaders to understand how systems operate today, where they are fragile, and how AI changes the risk surface.
Much of your time will be spent inside complex and imperfect system landscapes, identifying vulnerabilities, designing secure architectures, and hardening systems that were not originally built to support AI.
Your work will span the full lifecycle of an engagement. You will help shape technical approaches early, ensure that security and reliability are built into the system design, and implement the safeguards required for systems to operate in real-world conditions.
Many of the environments you will work in are not clean. Systems are incomplete, poorly integrated, or not designed with security in mind. Your role is to bring structure and resilience to these environments by building and hardening systems that can operate safely at scale.
At its core, this role is about one thing: making AI systems work in production without breaking trust.
You think AI-first, but with a strong understanding of how AI systems fail, break, and can be exploited in real-world environments.
You are comfortable working at the edge of AI capabilities, understanding risks such as prompt injection, data leakage, unsafe tool use, and model misuse, and designing systems that mitigate them.
You understand that AI systems are probabilistic and introduce new failure modes, and you design guardrails, evaluation loops, and controls that make them reliable and safe in production.
You are able to identify and harden weak points in existing systems, especially in environments where security and architecture were not designed properly from the start.
You have a strong software engineering foundation, with experience building and operating production systems in distributed or cloud-native environments.
You are comfortable working across authentication, authorization, data access, and system boundaries, ensuring AI systems interact safely with enterprise infrastructure.
You are pragmatic and execution-focused, able to improve security and reliability incrementally without blocking progress or over-engineering solutions.
You can translate messy, high-risk environments into secure, working systems, even when requirements are incomplete or constantly evolving.
You are comfortable working directly with engineers, architects, and security teams inside enterprise environments, aligning on practical solutions.
You bring a practical mindset around reliability, observability, and security, focused on what actually matters in production rather than theoretical completeness.
Intro Interview > 2 Technical deep-dives > Culture & Offer
