Applied AI Engineer
bug-bounty-switzerland · Zürich/Bern ·
- Work mode
- Hybrid
- Category
- AI engineering
bug-bounty-switzerland · Zürich/Bern ·
SignalFisher is the leading Security Testing Hyperscaler. With our Cyber Resilience Platform, we help regulated enterprises in financial services, critical infrastructure, and government stay ahead of evolving threats.
We’re headquartered in Switzerland, trusted by some of the most security-conscious organisations in Europe, and scaling fast.
We're building the operating system for enterprise security testing - a platform that turns security objectives into executable plans and translates findings into actionable insights. We have the vision and engineering foundation. Now we need an Applied AI Engineer to architect the intelligence layer that makes it real.
You'll own the AI capabilities that define how our platform thinks: memory systems that maintain context, orchestration logic that translates intent into action, and adaptive interfaces that serve every audience. You will build production-ready AI systems that solve real security challenges, so that enterprises can continuously test their defenses without exponentially scaling their security teams.
You'll architect and ship production-grade AI features that form the backbone of our security testing platform. This means:
Building our living semantic digital twin - creating persistent, evolving context that powers comprehensive understanding of enterprise environments
Evolving our orchestration engine - translating high-level security objectives into concrete, executable test plans and intelligently routing execution
Developing our adaptive reporting system - creating visually adaptive dashboards that synthesize context with technical findings to deliver actionable insights from engineer to board
Build AI features that work reliably in production - well-tested, maintainable, and ready for real-world use
Drive continuous innovation by exploring new LLM capabilities to keep our platform at the cutting edge
You'll work in cross-functional teams with full domain ownership:
Drive projects from ideation through production: prototype fast, validate assumptions, learn from real usage, and scale what works
Partner with other engineers, product, and stakeholders to solve customer security testing challenges through technical innovation
Build and maintain backend systems, AI pipelines, and integrations that power our platform
Balance rapid 0→1 iteration with the discipline needed for production-grade systems
Ship meaningful contributions within your first two weeks, then take on increasingly complex challenges
Proficiency in large-scale Python software development
Experience with C# and .NET Core or proven ability to learn a new programming language quickly
Passionate about applying AI to solve meaningful, real-world problems.
You’ve shipped and maintained AI/ML systems, not just built prototypes, and ideally in multiple domains
Strong experience with building software around LLMs: prompting, agentic orchestration, fault-tolerance, and integration of LLM parts with deterministic code.
Solid understanding of AI safety and alignment principles, including responsible AI development, bias mitigation, and ethical AI practices
Experience with cloud AI platforms such as Azure AI Foundry or AWS Bedrock
Strong skills in structured and independently-driven problem-solving. Able to work with incomplete information and rapidly testing hypotheses
You’re able to leverage AI Developer tools such as Copilot or Claude in your daily workflow
BSc or higher in computer science, cybersecurity math, physics or other related engineering field
Language requirements: English required; German a plus
Experience in cybersecurity or related industries
Experience in a growth stage startup and comfort with ambiguity
Prior development experience within large-scale or multi-tenant SaaS applications.
Experience with Durable Execution (Durable Functions, Prefect, Temporal)
Built AI-native interfaces using MCP apps, CopilotKit, AG-UI, or similar frameworks
Familiarity with frameworks like Agent Framework, AutoGen, or Semantic Kernel for agentic orchestration
Experience in secure tool usage, and (human) feedback loops for autonomous agents
Comprehensive understanding of various database technologies, including relational and non-relational systems
Familiarity with Azure services and deployment practices
Familiarity with CI/CD, DevOps, and infrastructure best practices
Reports to: CTO
Compensation: Competitive base + ESOP, aligned with seniority and impact
Work setup: Hybrid (Zurich/Bern)
We've built the foundation - a security testing platform with a proven orchestration engine, customer traction, and a clear product vision. What we need now is the AI engineering muscle to turn that foundation into intelligence: systems that remember context, reason about security objectives, and adapt how they communicate findings.
This role has leverage because security testing has always required human expertise to scope, interpret, and operationalize - until now. We're at the intersection of two realities: enterprises desperately need scalable security testing, and AI has finally reached the reliability threshold to deliver it end-to-end. You'll architect the intelligence that handles the complete workflow: translating business objectives into scoped test plans, orchestrating execution, and communicating findings that drive remediation decisions from engineer to board.
Your work unlocks what enterprises can't achieve today: continuous, intelligent security testing that scales with their environment, not their headcount.