• Co-own the underlying infrastructure that powers our OS, ensuring it is clean, consistent and well structured (you’ll work closely with domain experts, including our data & product engineers and designers) • Curate the skills, connectors, APIs and data layers that make building safe, fast and dependable • Ensure our foundation infra is accessible as a set of building blocks that others can build on with confidence • Quickly build key internal tools that help our Revenue team (Marketing, Sales and Client Success) deliver high-value work • Work closely with our Founder and Revenue team to identify problems and opportunities that should be solved with internal tooling • Iterate on tools based on real usage and feedback, treating internal teams as your customers • Design the foundations and workflows that allow non-technical colleagues to iterate on their tools using low-code platforms • Support and guide teams as they build, helping them get the most out of the platform without becoming a bottleneck • Approach internal tools as a product, grounded in a strong understanding of discovery and Jobs to be Done • Engage directly with users to understand their needs before building, rather than working from a list of requested features • Make pragmatic design decisions: interfaces don't need to be pixel-perfect, but are highly intuitive and genuinely useful

• Build new AI-powered product features from idea to production • Improve existing AI workflows for quality, reliability, latency, and user value • Design and implement LLM-based workflows, structured outputs, validation logic, and fallback behavior • Build evaluation loops, tests, and quality checks for AI-generated outputs • Integrate AI capabilities into existing product and backend systems • Work with commercial and open-source LLMs without being tied to one specific provider • Support self-hosted model workflows where they make sense for quality, speed, cost, or control • Debug AI feature failures across inputs, outputs, data, backend logic, and user flows • Use AI development tools as a core part of your daily workflow • Ship quickly while keeping production quality high

• Build new AI-powered product features from idea to production • Improve existing AI workflows for quality, reliability, latency, and user value • Design and implement LLM-based workflows, structured outputs, validation logic, and fallback behavior • Build evaluation loops, tests, and quality checks for AI-generated outputs • Integrate AI capabilities into existing product and backend systems • Work with commercial and open-source LLMs without being tied to one specific provider • Support self-hosted model workflows where they make sense for quality, speed, cost, or control • Debug AI feature failures across inputs, outputs, data, backend logic, and user flows • Use AI development tools as a core part of your daily workflow • Ship quickly while keeping production quality hi

Role Description We're a small fast-moving team building AI Agents to solve real-world cybersecurity challenges - things like threat detection, log analysis, and incident response automation. This isn't about flashy demos. We care deeply about correctness, reliability, and systems that actually perform under pressure. We're looking for a talented engineer with expertise taking complex systems from design all the way to production. The right candidate is excited to tackle difficult challenges using a blend of out-of-the-box thinking and proven software engineering best practices. Key Responsibilities - Design, develop, and productionize advanced agentic systems that: - Handle large volumes of security event data - Operate with resilience in noisy, real-world environments - Continuously evolve as new attack patterns and tools emerge - Improve and harden existing agentic systems - Work with LLMs in production environments, not just prototypes - Engineer robust context pipelines for large-scale data ingestion and reasoning - Optimize systems for performance, reliability, and failure handling - Evaluate and integrate new agent frameworks, tools, and approaches - Rapidly hypothesize -> build -> test -> validate -> iterate Qualifications - Strong Python (or equivalent modern language) engineering skills. - Deep understanding of language performance and internals (e.g., GIL, concurrency tradeoffs, memory constraints). - Proven experience building production-grade AI agents. Not just demos. Systems that run, recover, and scale. - Thorough understanding of LLMs and agentic systems. You understand how they actually work under the hood. - Strong context engineering skills. Able to curate, compress, and structure large datasets for effective LLM use. - Experience evaluating, testing, and monitoring agents and LLM interactions using the latest techniques or frameworks. - Experience handling large-scale high-volume data workflows. - Portfolio of shipped work (GitHub, case studies, or equivalent). - Bachelor of Computer Science/Engineering or above. - Must be a US Citizen. Requirements - Experience with cybersecurity tools (CrowdStrike, Splunk, Mandiant, etc.) - Familiarity with multiple agent frameworks (Claude Agent SDK, LangGraph, AutoGen, custom systems, etc.) - Experience evaluating tradeoffs between frameworks vs. custom orchestration. Benefits - At Deep Seas, we like to say that heart rates go down, careers take off, and security programs mature. - Our values provide the ultimate guide for our daily behavior and decisions: - We are client obsessed. - We stand in solidarity with our teammates. - We prioritize personal health and well-being. - We believe in the power of diversity. - We solve hard problems at the speed of cyber. - This is your chance to join a supportive crew of teammates and an industry-leading organization that values opportunities for growth. Information Security Responsibilities - Understanding and following DeepSeas’s information security policies and procedures. - Remaining vigilant and reporting any suspicious activity or possible weaknesses in DeepSeas’s information security. - Actively participating in DeepSeas’s efforts to maintain and improve information security.