About Spikerz

Spikerz secures enterprises’ external digital assets—protecting business accounts, privileged access and brand presence across platforms beyond the corporate perimeter.

As attackers weaponize AI, compromised identities, third-party access and ungoverned automation create new paths to account takeover and brand compromise. Spikerz addresses this expanding attack surface through enterprise-grade access governance, real-time threat detection and response.

About the role

Build the systems that turn threat research and security intelligence into production defenses. You’ll own critical backend and full-stack capabilities, working closely with Product, Security Research and AI teams.

What you’ll do

• Turn attack research into production defenses—build capabilities that discover exposed assets, uncover dangerous access relationships and interrupt account takeover paths.
• Engineer advanced browser automation and reverse engineer platform APIs to surface hidden permissions, reconstruct account state and execute precise protection workflows.
• Design distributed security systems that correlate account activity, identity changes and threat signals into actionable findings and coordinated response.
• Build AI-driven investigation workflows using LLMs, contextual retrieval and agents, with permission-bound tools, adversarial evaluations and independently verified actions.
• Drive security features from architecture to production, combining intuitive investigation interfaces with resilient backend services, tenant isolation and complete audit trails.

Core requirements

• 8+ years of backend/full-stack development, including ownership of production systems.
• Mandatory engineering experience at a cybersecurity product company.
• Strong TypeScript and Python skills, with experience developing modern frontend applications.
• Strong browser automation and API reverse engineering experience, including authentication, sessions, tokens and undocumented endpoints.
• Hands-on experience with RabbitMQ, Redis, Elasticsearch and Milvus.
• Strong foundations in distributed systems, secure API design, automated testing, CI/CD and production observability.

AI engineering requirements

• Hands-on experience integrating LLM APIs, structured outputs, embeddings, RAG and tool calling into application workflows.
• Practical use of AI development tools such as Claude Code, Cursor or GitHub Copilot, backed by independent code review, testing and security validation.
• Experience evaluating AI workflows through representative datasets, regression tests and tracing, with attention to accuracy, latency and cost.
• Understanding of prompt injection, sensitive-data exposure and agent permissions, with authorization enforced independently of model output.

Why Spikerz?

Own security capabilities used by global brands, influence core architecture and help define how enterprises defend external assets against increasingly automated threats.