
Maze · Remote (Europe)
SUMMARY OF THE ROLE: At Maze, we're building AI-powered vulnerability management at a moment when generative AI is fundamentally changing what's possible in cy...
At Maze, we're building AI-powered vulnerability management at a moment when generative AI is fundamentally changing what's
possible in cybersecurity. Our engineering team is small, fast, and technically elite — and we're hiring an Engineering Director
who is the same. This is not a coordination role. It is a senior technical leadership role for someone who earns respect by being
on the tools, thinks deeply about architecture, and happens to be exceptional at growing engineers and running a high-performance
org.
You'll work in close partnership with our CTO, Santiago, taking ownership of a growing set of teams and tech leads as we scale
from 20 to 35+ engineers. Your success will be measured the same way everyone's is at Maze: by the customer value and revenue
impact of what your teams ship — not by process compliance, headcount growth, or delivery cadence. You'll have genuine
accountability over a portion of the engineering org, with tech leads reporting to you, and you'll be expected to know your teams'
codebases well enough to make good decisions, spot problems early, and earn the trust of every engineer who works with you.
The person we're looking for has probably been the most senior technical person in a fast-moving 10–20 person engineering team — a
CTO, VP, or Head of Engineering at a startup — and is ready to bring that energy and credibility to a company with more firepower
behind it. If you want to stay close to the code, grow exceptional engineers, and help shape an org that will define how AI-native
security companies are built, this is that role.
teams (typically 3–5 engineers each), with tech leads reporting directly to you. Ensure every team has unambiguous priorities,
strong support, and everything they need to move fast.
your teams. We expect you to spend meaningful time understanding what each team is building — not as a gatekeeper, but as a
trusted technical voice who can contribute, challenge, and improve.
tech leads and senior engineers in your teams. Build the kind of trust with engineers that comes from genuinely knowing their
work, their growth areas, and their ambitions — not from generic 1:1s.
teams aligned and unblocked. Keep it lightweight, decision-focused, and in service of engineering velocity — not process for
its own sake.
processes to closing exceptional candidates. The quality of who we hire is one of the highest-leverage things either of us can
do.
and evolve how we operate as the team doubles. We grow leaders from the inside where we can — you'll be central to identifying,
developing, and empowering the next generation.
high standards across the org — without letting process replace judgment.
architecture discussions, code reviews, and technical decisions. You don't need to be the best coder in the room, but you need
to be in the room for the right reasons.
Engineering at a startup — or a tech lead in a similarly fast-moving environment — where you were accountable for both
technical outcomes and the people delivering them. You know what it looks like to lead 10–20 engineers, not just manage them.
growing engineers into leaders. You've had hard conversations, made difficult calls, and built cultures where high performance
and high support coexist.
reading a status update. You see "staying technical" as a feature of your leadership style, not a tension with it.
things out — not environments where scale compensates for speed. You know how to get a lot done with a little.
candidates — and you have strong opinions about what great looks like.
they're building what they're building, not just how.
quickly.
led teams building on top of these technologies.
today. The engineering challenges are genuinely hard, the domain matters, and we're early enough that the architectural
decisions you make will define the platform for years.
multiple acquisitions and an IPO. We hire for quality over speed and it shows.
organisations against real attacks. The mission isn't decorative.
blank sheet of paper, in an era where agentic coding tools are changing what small teams can accomplish. You'll shape that from
the start.
day one, with a direct partnership with Santiago and significant equity upside as we scale.
SUMMARY OF THE ROLE: As a Product Designer at Maze, you'll define what product design looks like for AI agents in cybersecurity — a problem space where the design patterns don't exist yet. This is an early-hire role at a well-funded Series A startup building at the intersection of generative AI and security, and you'll own the product surface end-to-end while working directly with our Head of Product, engineering, and founders. The product challenge is genuinely new. Our AI agents investigate vulnerabilities autonomously, surface findings with real context, and collaborate with security teams to cut through noise. Your job is to design how humans and agents work together — how trust gets built, how decisions get communicated, how complex security workflows become understandable. There's no playbook for this. You'll create one. This role suits someone who operates closer to a product director than a screen-shipper — driving direction, influencing strategy, and making business-impact calls, alongside the visual craft to deliver them. You'll be using AI tools daily to move faster, but your craft is the floor: every design choice should hold up on its own merits, independent of how it was generated. Success looks like a design system shipped and adopted across the product, and concrete product outcomes — feature adoption, POC-to-customer conversion, and customer satisfaction with the experiences you ship. YOUR CONTRIBUTION: * Define AI-Agent UX Patterns: Design how security teams collaborate with autonomous AI agents — how investigations get presented, how trust is established, how humans steer the agent without slowing it down. You're inventing patterns, not applying existing ones. * Drive Product Direction, Not Just Design: Operate as a product-led designer — shaping roadmap, challenging requirements, influencing leadership with research and business reasoning. The bar is "what should we build, and why" alongside "how should it look." * Own the Product Surface End-to-End: Take features from problem framing through shipped product, working in tight partnership with PMs and engineers — including backend. Run discovery, prototype rapidly, validate with customers, and stay close to implementation. No throwing designs over the wall, no shipping around the engineering team. * Build the Design System: Create and scale a component-based design system that becomes the foundation for everything we ship. Establish patterns for AI-human collaboration that the team can build on as we grow. * Pioneer AI-Assisted Design Workflows: Use AI tools to accelerate ideation, prototyping, and exploration — and develop the methodologies the rest of the team will adopt. Your daily workflow is itself a contribution. * Translate Research Into Design: Run customer research, talk to security teams directly, and turn what you learn into shipped product. Use AI-assisted analysis to move from insight to prototype in days, not weeks. * Set the Quality Bar: Establish what "good" looks like for product design at Maze across craft, consistency, and customer impact — as the foundation for a design team that scales behind you. WHAT YOU NEED TO BE SUCCESSFUL: * Visual Craft for Data-Dense UI: A portfolio that holds up to detailed scrutiny — strong colour theory, deliberate visual hierarchy, considered information architecture for complex workflows. This is the bar, not a nice-to-have. Your interview will dig into specific design choices and why you made them. * Product Design Track Record: 4-7 years of professional product design experience, with shipped work in B2B SaaS. We're flexible on years; demonstrated craft and clear ownership matter more than time served. * Data-Heavy B2B Interfaces: Direct experience designing for complex workflows, dense data, and technical audiences. Dashboards, investigation tools, developer products, security platforms — the kind of UI where information density and decision support actually matter. * AI as Tool, Not Crutch: You use AI tools (Figma AI, Cursor, v0, Midjourney, ChatGPT/Claude, etc.) as part of your daily workflow and can speak credibly to what they're good for and where they break down. Critically, every design choice you ship should hold up on its own — AI accelerates your work, it doesn't substitute for foundational craft. * Product-Strategic Thinking: Track record of driving product direction, not just executing on briefs. You've influenced what to build with research, framed problems for leadership, and made business-impact calls — ideally in environments where you operated without a dedicated PM. * Deep Engineering Collaboration: Demonstrable history of shipping work in tight partnership with engineers — including backend. Pairing on implementation, working in design tokens, understanding the systems your designs land in, building consensus rather than shipping around resistance. * Design Systems Experience: Background building or meaningfully contributing to a design system in a production product. You think in components, tokens, and patterns, not one-off screens. * Customer-Led Approach: Comfortable running discovery directly with users, synthesising what you hear, and using that to make calls about what to build. You don't wait for research to be handed to you. * Nice to haves: * Experience designing for cybersecurity, developer tools, or other technical product domains * Background designing agentic or AI-native product experiences (not just AI features bolted onto existing products) * Early-stage startup experience where you've operated without a manager or established design function WHY JOIN US: * Define a New Design Space: AI agents in security is a genuinely new problem. The interaction patterns, trust models, and workflows don't exist yet — you'll create them. The work you do here will influence how this entire category gets designed. * Fast-Track to Design Leadership: This is a founding-trajectory role and we're hiring for someone who wants a long-term home, not a stepping stone. As the team scales, the natural path is IC → Lead → Head of Design. If you have leadership ambitions, you'll have the runway to grow into them. If you'd rather stay deeply hands-on, the IC scope grows with the product. * Ambitious Challenge: We're using generative AI (LLMs and agents) to solve one of the most pressing problems in cybersecurity — the gap between vulnerability findings and meaningful action. You'll be designing at the cutting edge of this field. * Expert Team: Work alongside 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. * Impactful Work: Cybersecurity is a force for good. The experiences you design will directly affect how security teams protect organisations worldwide. * Build an AI-Native Company: We're building a new company in the AI era with the opportunity to design everything from the ground up — including how the design function itself works. You'll help pioneer AI-assisted design practices and set new standards.
Summary of the Role: As Product Engineer (Full Stack) at Maze, you'll be the technical force behind our customer-facing product experience, owning the complete stack from UI to API while moving at startup velocity. This is a unique opportunity to join as one of the early engineering team members of a well-funded startup building at the intersection of generative AI and cybersecurity. You'll work alongside our full stack product team with significant autonomy, owning your own API layer that powers the React application, enabling you to move fast and deliver exceptional experiences without dependencies or blockers. You'll take full ownership of feature development from concept to production, building both the elegant UI components that security teams interact with daily and the robust API infrastructure that makes it all work. Your success will be measured by delivery velocity, product quality, autonomous execution, and the customer experience you create—not by process adherence or ticket completion. This role is perfect for a hands-on full stack engineer who has thrived in fast-paced B2B SaaS environments, values independence and ownership, and wants to build something extraordinary with a modern tech stack from the ground up. Your Contributions to Our Journey: * Own Product Feature Development: Take complete ownership of features from front-end UI through to API implementation and database layer, delivering end-to-end functionality that delights customers and drives product adoption * Build with Modern Front-End Excellence: Craft exceptional user experiences using React, TypeScript, TailwindCSS, and the TanStack ecosystem (Router, Query, Table), creating intuitive interfaces for complex security workflows with attention to detail and performance * Design and Maintain API Infrastructure: Build and own performant REST APIs using our Python/FastAPI backend, ensuring scalable, maintainable services that power the front-end while maintaining clean architecture and performance optimization * Drive Autonomous Execution: Operate with high independence and startup energy—identify what needs building, make technical decisions quickly, and execute without waiting for perfect requirements or extensive process * Optimize for Performance and Scale: Continuously improve application performance across the stack, from database query optimization to front-end rendering efficiency, ensuring our platform scales elegantly as we grow * Contribute to Architectural Decisions: Participate in technical discussions and architectural planning, bringing your experience to help shape our front-end architecture and potentially grow into owning architectural decisions as the team scales * Balance Speed with Quality: Move at startup pace while maintaining high standards—ship features rapidly, gather feedback, iterate quickly, but never compromise on code quality or customer experience What You Need to Be Successful: * Proven Full Stack Product Experience: 6+ years building production applications with strong command of both front-end and back-end development—you must be genuinely skilled at both, not primarily one with dabbling in the other * Strong TypeScript and React Expertise: Deep, hands-on experience with TypeScript and React (or other modern component-based frameworks) in production environments, with strong understanding of component architecture, performance optimization, and modern patterns * Performant RESTful API Development: Proven track record building performant RESTful APIs with server-side frameworks, with experience designing scalable API architectures, optimizing endpoint performance, and building maintainable backend services * B2B SaaS Background: Direct experience in B2B SaaS product companies where you've built features for business users, understanding the unique requirements of enterprise product development and customer-facing applications * Database Performance Intuition: Strong understanding of database interactions and query optimization—you instinctively know when a query might blow up and how to structure data access for performance at scale * Startup Velocity Mindset: Thrives in fast-paced, ambiguous environments with bias for action—you "just go get it, go do it" without waiting for perfect specs, comfortable making pragmatic technical decisions quickly * Attention to Detail with Speed: Exceptional balance of moving fast while caring deeply about customer experience and code quality—you build things right the first time while maintaining velocity * Collaborative Independence: Comfortable working autonomously and owning your work end-to-end, while also collaborating effectively with designers, product managers, and other engineers when needed * Nice to Haves: * Python and FastAPI experience for our backend stack * Kubernetes/EKS experience for understanding our deployment environment and infrastructure * Temporal workflow orchestration experience for complex, distributed workflows * PostgreSQL optimization skills and experience with database performance tuning at scale * Experience integrating LLMs into applications, understanding how to build AI-powered features into production products * Experience with our specific front-end stack: TailwindCSS, TanStack ecosystem (Router, Query, Table), shadcn/ui, Radix UI * Infrastructure knowledge and comfort working with cloud platforms or infrastructure-as-code tools * Design system or component library development experience * Background at technical B2B SaaS companies where product velocity and customer experience were primary drivers Why Join Us: * Ambitious Challenge: We're using generative AI (LLMs and agents) to solve some of the most pressing challenges in cybersecurity today. You'll be building the product experiences that security teams interact with daily, creating intuitive interfaces for breakthrough AI-powered solutions. * 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. * Impactful Work: Cybersecurity is a force for good - helping to stop cyber attacks ultimately helps deliver better outcomes for all of us. Your work will directly enable security teams to protect organizations worldwide from real threats. * Build an AI-Native Company: We're building a new company in the AI era with the opportunity to design everything from the ground up - you'll work with a modern, carefully chosen tech stack and help establish engineering practices that scale with us through hypergrowth. * Technical Ownership and Growth: True end-to-end ownership with your own API layer, freedom to make architectural decisions, and opportunity to grow into front-end architectural leadership as we scale the team and product.
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