Backend Engineer (AI Agents)

Maze

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.

Maze

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.

myTomorrows

About myTomorrows  myTomorrows is a global health tech company dedicated to breaking down barriers for patients seeking treatment options.    We strive to enable earlier and better treatment access by bridging the gap between those searching for possible options, and the companies who develop them. We work closely with patients, healthcare professionals, trial sites, patient advocacy groups, and BioPharma – connecting key stakeholders in the drug development ecosystem.    We’ve developed a cutting-edge AI-powered technology platform that simplifies and streamlines access to drugs in development. To support our users and clients, we have a range of industry-expert specialized teams ready to help. Our services include clinical trial patient recruitment, Expanded Access Program management and Real-World Data collection.    With a global footprint spanning 134 countries, to date we’ve supported over 17,000 patients, 3,000 physicians and 350 sites, earning the trust of 60+ BioPharma companies. In October 2025, we closed a €25M investment with Avego Healthcare Capital to fuel our global ambitions and scale the business.   Join us in shaping the future of treatment access - making tomorrow’s therapies accessible for people who need them today.  THE OPPORTUNITY: APPLIED AI ENGINEER As Applied AI Engineer at myTomorrows, you will help us become more AI-native in how we work, build, and deliver value to patients, physicians, trial sites and (bio-)pharma partners. Your primary focus is internal: the teams, workflows, and operational processes inside myTomorrows. This is not a pure research role, and it is not a “prompt engineer” role. You are an experienced software engineer who knows how to build reliable systems, and who is experienced with the possibilities created by LLMs, agents, AI-assisted coding, retrieval, workflow automation, and internal tooling. You will work as part of our AI Acceleration initiative: a small, high-leverage team focused on safely applying AI across the organization. You embed with internal teams, e.g. Operations, Regulatory, Commercial, Marketing, to find the highest-leverage points of intervention, build production-ready solutions, and leave behind systems that teams can own and operate without you. A key part of the role is not just building things yourself, but helping myTomorrows learn how to build with AI. You will help define reusable patterns, guardrails, evaluation approaches, and engineering practices so that AI-assisted work becomes reliable, secure, maintainable, and scalable. Given that most of our team is located in the Netherlands, we only consider candidates for this position who live within commuting distance of our office in Amsterdam. HOW YOU WORK Each engagement follows the model of a “Forward Deployed Engineer”: Insertion. When you start a mission, you sit with the people who do the actual work: not the people who manage them. You watch, you ask questions, and you map what's really happening: the tools, the manual steps, the tribal knowledge, the workarounds that nobody questions anymore. Your first deliverable is not code. It is a situational awareness map. Discovery. From that map, you identify the highest-leverage intervention point: not the most technically interesting problem, but the one that, if solved, would make the most visible difference to the most people in the shortest time. Delivery. You build production-capable solutions on real data with measurable success criteria defined upfront. You identify an internal champion in week one who will own the system after you leave, and you embed them in the work from the start. Handoff. You leave behind a running system, not a prototype. You leave behind an eval framework and runbook so the system doesn't rot. And you leave behind an AI substrate — connectors, pipelines, and workflow patterns — that makes the next mission faster. WHAT YOU’LL DO IN THIS ROLE * Build production-capable AI-enabled internal tools, workflow automations, agents, and integrations that solve real business problems by embedding with internal teams. * Use modern LLM capabilities such as structured outputs, tool calling, retrieval-augmented generation, agentic workflows, prompt/context engineering and creating evals. * Help teams translate ambiguous business problems into clear, testable, AI-assisted delivery plans. * Build backend services, APIs, integrations, and internal applications using modern software engineering practices. * Work closely with Product, Engineering, QA, DevOps, Data, Legal, Privacy, and Security to ensure AI-built software is safe, secure, observable, and maintainable. * Design and implement evaluation approaches for AI systems, including test sets, human review loops, quality criteria, failure mode analysis, and monitoring. * Create reusable playbooks, templates, prompts, Skills, MCPs and examples that help other teams adopt AI effectively. * Help assess whether a solution should remain a lightweight internal tool, be transferred to a business owner, be hardened by Product & Engineering, or be stopped. * Stay up to date with the rapidly evolving AI engineering landscape and translate relevant developments into practical opportunities for myTomorrows. WHAT YOU BRING TO THE TABLE * 3+ years of professional software engineering experience, ideally in a product, platform, backend, fullstack, startup, or scale-up environment. * Strong software engineering fundamentals. You have built and maintained real systems before (and before vibe-coding was thing), and you know that shipping reliable software is about more than generating code. * Experience with backend development, ideally with Python and modern API development. * Experience with relational databases such as MySQL, PostgreSQL, or Oracle. * Experience with cloud platforms such as AWS, Azure, or GCP. * Strong understanding of testing, code review, observability, security, documentation, and maintainability. * Hands-on experience with the modern essentials of AI agents, agentic engineering and AI coding tools: LLM APIs, agents, RAG, MCPs, Skills, workflow automation and AI-enabled product development. * Ability to work independently in ambiguous environments, while communicating clearly with technical and non-technical stakeholders. * Strong product sense: you care about solving the actual problem, not just using the newest tool. * A pragmatic startup mentality: you can move fast, make sensible trade-offs, and know when to prototype, when to harden, and when to stop. * Excellent English communication skills. NICE TO HAVE * Experience with FastAPI, Pydantic, SQLAlchemy, uv, ruff, pre-commit, GitHub Actions, or similar tools. * Experience with AWS-native architectures, infrastructure as code, Terraform, serverless, Kubernetes, or cloud-native platform work. * Experience with frontend development, especially Angular, React, TypeScript, or fullstack personal projects. * Experience building internal tools, developer tools, workflow automation, or operations tooling. * Experience with AI evaluation frameworks, model monitoring, prompt/version management, or human-in-the-loop review systems. * Experience with healthcare, pharma, clinical research, regulated environments, privacy-sensitive data, or compliance-heavy workflows. * Experience with tools such as Claude Code, Codex, Cursor, GitHub Copilot, LangChain/LangGraph, LlamaIndex, n8n, or similar AI/workflow platforms. WHAT SUCCESS IN THE FIRST 6 MONTHS LOOKS LIKE * You have built trust with Product, Engineering, DevOps, Data, and business stakeholders by delivering useful AI-enabled solutions without creating unmanaged technical debt. * You have delivered 2-3 high-impact AI Acceleration missions, such as an internal tool, workflow automation, agentic engineering improvement, or AI-assisted product delivery pilot. * You have shipped production-capable software with clear ownership, tests, documentation, observability, and security considerations. * You have created reusable templates, prompts, scripts, or examples that other teams can use. * You have helped teams understand where AI is genuinely useful, where it is not ready yet, and what guardrails are needed. * You have contributed to a culture where AI-assisted engineering is judged by objective production outcomes: correctness, security, maintainability, observability, and business value. CURRENT TECH STACK We are fully cloud-native, leveraging AWS and adopting a lean, API-first product development approach driven by modern cloud technologies and thoughtful design practices. Our current Backend Engineer posting describes a stack including Python, FastAPI, Pydantic, SQLAlchemy, MySQL/PostgreSQL, Angular, GitHub Actions, Renovate, ruff, uv, pre-commit, Docker, Docker Compose, Kubernetes, Terraform, DynamoDB, and Neo4j. As Applied AI Engineer focused on internal use cases, you will often work in lighter-weight stacks like scripts, Skills, MCPs, APIs, workflow tools, internal dashboards rather than full product infrastructure. Familiarity with the product stack is useful context, but your day-to-day tooling will be shaped by the mission. WHAT WE OFFER * Impactful work that helps patients gain access to potentially lifesaving treatments. * A unique opportunity to help define how a HealthTech scale-up becomes AI-native. * International work environment, scale-up energy, and a flat organizational structure that encourages creativity and accountability. * Competitive salary, annual performance bonus, and an Employee Stock Option Plan. * Great career development opportunities in a fast-growing company. * Learning and development budget alongside internal knowledge-sharing sessions. * Attractive pension plan, full premium covered by myTomorrows. * Hybrid working model. * Policies to support working parents. * Healthy lunch at the thriving Amsterdam office. * Unlimited access to professional guidance by certified psychologists via OpenUp. * Monthly events hosted by our vibrant Culture Club as well as an annual myTomorrowland company-wide celebration. Equal opportunities myTomorrows is an Equal Opportunity Employer and, beyond upholding discrimination-free practices, we are committed to cultivating a workplace where difference and diversity are protected and celebrated. The best work comes from our best selves, and we go to great lengths in supporting our team members to be just that.