Product Engineer (Full Stack)

Maze

SUMMARY OF THE ROLE: As ML Engineer at Maze, you'll be the technical leader driving our machine learning infrastructure from experimentation to production, ensuring our AI-powered cybersecurity solutions deliver measurable impact for customers worldwide. This is a unique opportunity to join as one of the early engineering team members of a well-funded startup building breakthrough applications of LLMs and AI agents in cybersecurity. You'll take full ownership of evaluation frameworks, production ML pipelines, and cross-team ML integration, working closely with our CTO and product teams to transform cutting-edge AI research into robust, scalable solutions that solve real security challenges. Your success will be measured by agent performance improvements and product innovation impact, not just technical metrics. This role is perfect for a hands-on ML engineer who has scaled production ML systems across multiple companies, thinks like a product builder, and wants to drive the actual productionization of LLMs and ML to solve significant pain points. YOUR CONTRIBUTIONS TO OUR JOURNEY: * Build Production-Grade Evaluation Systems: Design and implement comprehensive evaluation frameworks that measure agent performance, track improvements over time, and ensure our AI systems deliver consistent value to customers * Drive Experimentation-to-Production Pipeline: Own the entire ML lifecycle from prototype to production, building scalable systems that enable rapid iteration while maintaining reliability and performance in customer environments * Enable Cross-Team ML Integration: Work closely with product teams to seamlessly integrate ML capabilities into customer-facing features, ensuring technical excellence translates into user value and product differentiation * Optimize AI Agent Performance: Continuously improve our AI agents through systematic experimentation, prompt engineering, and architectural enhancements, measuring success through customer impact and system performance * Scale ML Infrastructure: Build the foundational ML systems, monitoring, and tooling that will support our growth from startup to scale, ensuring we can deploy new capabilities quickly without compromising quality * Partner with Engineering Leadership: Collaborate directly with our CTO through regular check-ins and strategic alignment while operating with high autonomy and self-direction in day-to-day execution * Mentor Through Excellence: Provide natural mentorship to junior ML engineers through code reviews, technical guidance, and sharing practical experience from building production ML systems WHAT YOU NEED TO BE SUCCESSFUL: * Proven Production ML Experience: 6+ years building and scaling machine learning systems in production environments, with hands-on experience moving from experimentation to customer-facing deployments * Deep Neural Networks Foundation: Strong background in classical neural networks and deep learning fundamentals before specializing in modern LLMs and transformer architectures - you understand the foundations, not just the latest tools * Product-Focused ML Mindset: Experience building ML systems that solve real business problems, with a track record of integrating classification, prediction, or recommendation systems into actual products customers use * Multi-Company Perspective: Experience across multiple organizations (scale-ups, startups, or combination), giving you practical knowledge of what tools to build vs buy and how to avoid over-engineering * Technical Versatility: Strong Python skills with flexibility across ML frameworks and tools - comfortable adapting to our stack including LangChain, evaluation frameworks, and workflow orchestration tools like Temporal * Self-Directed Leadership: Ability to operate autonomously while maintaining close alignment with leadership, comfortable with frequent check-ins but capable of driving projects independently * Cross-Functional Collaboration: Experience working closely with product teams and potentially customers, translating technical capabilities into business value and user experiences * Nice to Haves: * Experience with AI agents, LLMs, or modern generative AI applications * Cybersecurity domain knowledge or experience applying ML to security challenges * Background at ML-first companies or organizations where ML was core to the product * Experience with modern MLOps practices and cloud-based ML infrastructure * Track record of optimizing model performance and controlling AI system costs WHY JOIN US: * Real-World AI Impact: Drive the actual productionization of LLMs and machine learning to solve significant cybersecurity pain points - your work will directly protect organizations from real threats, not just optimize internal metrics * Technical Leadership Opportunity: Work directly with our CTO on cutting-edge ML infrastructure while having the autonomy to shape technical decisions and build systems that scale with our hypergrowth * Expert Team Partnership: Join a team of hands-on leaders with experience in Big Tech and Scale-ups, including leadership team members who have been part of multiple acquisitions and an IPO * Build the AI-Native Future: Shape how generative AI transforms cybersecurity from the ground up, establishing ML practices and technical standards that will define the industry * Multiple Growth Pathways: Clear opportunities to grow into Head of ML Engineering, become a domain technical lead, move into customer-facing technical roles, or excel as a senior individual contributor - the choice is yours based on your interests and our needs * Breakthrough Technology: Work at the intersection of generative AI and cybersecurity, building solutions that leverage the latest advances in LLMs and AI agents to solve some of the most pressing challenges security teams face today

Maze

Summary of the Role: As an Engineer at Maze, you'll play a pivotal role in shaping our product, with significant focus on the development of AI Agents and ML systems. You will have the unique opportunity to design, build, and scale a product from the ground up, influencing everything from architecture decisions to ML integrations and the overall user experience. This is an exciting chance to be at the core of our technical team, driving innovation in AI-powered cybersecurity solutions and ensuring seamless integration across the stack. Your Contributions to Our Journey: * AI Agents: Play a pivotal role in the development and scaling of complex AI Agents to tackle some of the biggest challenges in cybersecurity. * Architect and Develop: Design and implement backend systems that effectively support agentic workloads, ensuring they are scalable, maintainable, and secure. * End-to-End Ownership: Take ownership of the entire development lifecycle, from concept and design to deployment and maintenance. * Integrate Seamlessly: Work closely with other engineers, our designer/product manager to ensure seamless integration of new features and services. * Optimize for Performance: Continuously monitor and improve application performance, security, and scalability. * Establish Best Practices: Define and enforce coding standards, best practices, and documentation to maintain high code quality. * Rapid Prototyping: Quickly prototype and iterate on new features, adapting to user feedback and changing requirements. * Mentor and Lead: As the team grows, mentor junior engineers and lead by example in technical discussions and code reviews. What You Need to Be Successful: * Extensive Experience: 7+ years of experience in backend development * Backend Mastery: Strong experience with backend development, including RESTful API design, database management, and server-side frameworks (e.g., Python). * ML/AI Understanding: Working knowledge of machine learning principles and experience integrating LLMs or other AI services into production applications. Familiarity with tools like LangChain, LlamaIndex, or similar frameworks is a plus. * Cloud Experience: Familiarity with cloud platforms (e.g., AWS) and their ML services, along with DevOps practices, including CI/CD and containerization (e.g., Docker, Kubernetes). * Problem-Solving Skills: Strong analytical and problem-solving abilities, with a focus on delivering robust and scalable solutions. * AI Systems Architecture: Understanding of how to architect systems that effectively leverage AI capabilities while maintaining performance and reliability. * Collaborative Spirit: Excellent communication skills and the ability to work effectively in a cross-functional team. * Agility and Adaptability: Comfort working in a fast-paced startup environment with the ability to pivot and adapt as needed, particularly in the rapidly evolving AI landscape. Why Join Us: * Ambitious Challenges: We are using Generative AI (LLMs and Agents) to solve some of the most pressing challenges in cybersecurity today. You’ll be working at the cutting edge of this field, aiming to deliver significant breakthroughs for security teams. * Expert Team: We are a team of hands-on leaders with deep experience in Big Tech and Scale-ups. Our team has been part of the leadership teams behind multiple acquisitions and an IPO. * Impactful Work: Cybersecurity is becoming a challenge to most companies and helping them mitigate risk ultimately helps drive better outcomes for all of us.

Maze

SUMMARY OF THE ROLE: As a Security Research Engineer at Maze, you'll be at the forefront of defining what constitutes real security risk in the age of AI-powered vulnerability detection. This is a unique opportunity to join our growing security research team at a well-funded startup building at the intersection of generative AI and cybersecurity, where your security expertise directly shapes how our AI models understand and prioritize cloud security threats. You'll spend the majority of your time as the expert human-in-the-loop, analyzing cloud vulnerability findings from our AI systems, conducting deep research to validate and contextualize threats, and creating the authoritative labels that train our models to distinguish critical risks from noise. Working alongside other security researchers, you'll help scale our labeling operations while providing critical input into product development decisions based on real-world threat patterns you discover. This role is perfect for a security researcher who wants to pioneer the future of AI-assisted threat detection, loves diving deep into cloud security vulnerabilities, and wants to see their security insights amplified through cutting-edge technology while contributing to a growing team. YOUR CONTRIBUTIONS TO OUR JOURNEY: * Scale Expert Data Labeling Operations: Lead high-volume vulnerability labeling and validation work as the authoritative voice on threat severity, reviewing and categorizing cloud security findings from our AI models to create the high-quality training data that powers our platform * Drive Product Development Through Research Insights: Translate patterns and insights from your labeling and research work into actionable product improvements, working directly with engineering and product teams to enhance detection capabilities and user experience * Collaborate with Security Research Team: Work closely with fellow Security Research Engineers to maintain consistency in labeling standards, share research findings, and collectively improve our vulnerability assessment methodologies * Deep Vulnerability Research: Conduct comprehensive research into cloud vulnerabilities affecting EC2 images, Docker containers, and cloud infrastructure, investigating true/false positives, analyzing business impact, and building proof-of-concepts to validate threat scenarios * Enhance AI Model Accuracy: Provide expert feedback through our labeling tools that improves our AI models' understanding of vulnerability context, helping them learn to prioritize threats like a seasoned security researcher * Technical Investigation and Analysis: Create detailed technical writeups about exploitation techniques, attack vectors, and remediation strategies for cloud vulnerabilities, turning complex security research into actionable intelligence * Leverage External Security Intelligence: Integrate insights from CVE databases, security advisory feeds, and threat intelligence sources to enrich vulnerability findings with broader context and emerging threat patterns * Contribute to Thought Leadership: Support our external presence through technical blog posts, security videos/podcasts, and occasional conference presentations, sharing insights from your research WHAT YOU NEED TO BE SUCCESSFUL: * Security Research Expertise: 5+ years of hands-on security experience with proven vulnerability research background, comfortable investigating complex security issues and building proof-of-concepts to validate findings * Cloud Security Mastery: Deep knowledge of AWS security, cloud infrastructure vulnerabilities, container security, and cloud-native attack vectors, with hands-on experience securing cloud environments at scale * Technical Investigation Skills: Strong coding and scripting abilities (Python, Go, or similar) for automating research tasks, building validation tools, and creating proof-of-concept exploits * Analytical Excellence: Proven ability to analyze complex security data, distinguish between critical threats and false positives, and communicate technical findings to both technical and business audiences * Product Mindset: Experience translating security insights into product requirements, with ability to identify patterns across vulnerabilities that inform strategic product decisions * External Intelligence Integration: Experience working with vulnerability databases, security advisory feeds, and threat intelligence sources to contextualize and prioritize security findings * Collaborative Mindset: Strong communication skills and ability to work effectively with security research peers, AI/ML teams, and product stakeholders, translating security domain knowledge into actionable improvements * High-Volume Execution: Comfort with systematic labeling work while maintaining accuracy and attention to detail, balancing speed with quality in fast-paced environments * Nice to haves: * Experience with AI/ML security or working with AI-generated security findings * Background at security tooling companies or building security products * Expertise in specific vulnerability research methodologies and frameworks * Open source contributions to security tools or research projects * Previous content creation experience in security (blogs, talks, research papers) * Industry certifications (CISSP, OSCP, AWS Security, etc.) WHY JOIN US: * Ambitious Challenge: We're using generative AI (LLMs and agents) to solve some of the most pressing challenges in cloud security today. You'll be defining how AI understands and prioritizes vulnerabilities, working at the cutting edge of AI-powered threat detection. * Expert Team: We are a team of hands-on leaders with experience in Big Tech and Scale-ups. Our team has been part of the leadership teams behind multiple acquisitions and an IPO. * Growing Security Research Function: Join a collaborative security research team where you'll work alongside other experts, share insights, and collectively shape how our AI platform understands security threats at scale. * Impactful Work: Your security research and labeling work will directly improve how thousands of organizations understand and respond to cloud security threats, scaling expert security knowledge through AI to protect the entire ecosystem. * Product Influence: Your day-to-day research insights will directly influence product strategy and development, giving you a voice in building the next generation of AI-powered security tools. * Pioneer AI-Native Security: Help establish the gold standard for AI-assisted vulnerability research, defining how human security expertise enhances machine learning models in the cybersecurity domain.