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.

• As an AI Developer (m/f/d) at Axontic, you will elevate our products with Large Language Models. • Together with our team, you will design innovative features that delight customers and revolutionize everyday email workflows. • Develop smart solutions around LangChain, LangGraph & Co. that automate email workflows and provide personalized assistance. • Build high-performance AI systems on Microsoft Azure, implement CI/CD for models, and ensure maximum availability through monitoring and optimization. • Independently evaluate new LLM frameworks, modern web stacks (Node.js, Nest.js, FastAPI) and vector databases (Weaviate, Qdrant, Azure AI Search) — from prototype to production.

• Design, develop and deliver AI-powered features end-to-end: from proof of concept to production on our Partner's stack (Angular, Node/TypeScript, PostgreSQL, Azure) • Evaluate and integrate AI/ML services, APIs, and open-source models to solve real customer problems (document processing, root-cause analysis, ERP/MES integrations) • Shape the AI/ML tech stack with real ownership over tools, frameworks, and architecture • Build and maintain eval frameworks to ensure AI outputs meet quality, reliability, and safety standards • Collaborate with product and engineering, identify high-impact AI opportunities, and grow AI competency across the team

• Design and develop edge machine learning systems that improve the autonomy and safety of our construction robots • Build scalable ML infrastructure for model training, validation, deployment, and monitoring • Develop and optimize computer vision and sensor fusion models for construction environments • Analyze large-scale operational datasets to improve model performance and reliability • Improve object recognition, scene understanding, and autonomous decision-making systems • Integrate cloud-based commercial and open-source AI tools into our autonomy stack