Identify systemic security risks across applications, on-prem infrastructure, cloud environments, internal platforms, and software development processes.
Perform security architecture reviews for existing and new systems.
Work directly with engineering teams to identify security weaknesses early in the software development lifecycle and design practical ways to address them.
Partner with our SOC to improve detection capabilities, analyze attack patterns and incidents, and translate findings into better detection rules, security controls, and long term architectural improvements.
Design and help implement security controls, tools, automation, and services that can be reused across engineering teams.
Define and evolve technical security standards, engineering guidelines, reference architectures, and security best practices.
Review complex technical designs and provide actionable security recommendations.
PythonJavaKubernetes+3 more
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About RTB House
RTB House pioneers Deep Learning AI to transform digital advertising. They leverage proprietary algorithms to optimize ad campaigns for major brands. Their platform helps businesses maximize conversions and acquire new customers. Operating in over 90 markets, RTB House delivers end-to-end AdTech solutions. They focus on first-party advertising and continuous innovation.
How We Work
RTB House embraces flexible work arrangements, including full remote options. You can choose to work from home or from their offices in Warsaw or Cracow. They value a healthy work-life balance and provide a home-office stipend. Team members are encouraged to think creatively and take ownership. There is a strong focus on continuous learning and professional growth. This dynamic environment supports career advancement and cross-functional collaboration. RTB House fosters a workplace where individuals feel valued and empowered.
Engineering at RTB House
RTB House's core is a proprietary ad-buying engine powered entirely by Deep Learning AI. This engine processes over 20 million requests per second globally. Engineers tackle challenges in high performance, scalability, and observability for ad display and tracking. You will build internal tools and intelligent agents to boost engineering productivity. The team evaluates novel Agentic AI systems, LLMs, and Model Context Protocols (MCPs). This involves making pragmatic build-vs-buy decisions for complex solutions. Their tech stack includes Python, Java, Scala, PyTorch, and modern web frameworks. They also utilize Google Cloud Platform, Kubernetes, Kafka, and Elasticsearch. They are actively contributing to cookieless solutions like the Chrome Privacy Sandbox.
Why Join Us
Build with Deep Learning AI to solve complex, large-scale problems in AdTech.
Work in a truly international environment across 90+ markets.
Contribute to a product with a 99% client retention rate.
Enjoy flexible work-life balance with remote or hybrid options.
Benefit from internal training programs and an annual budget for skill development.