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.

Databricks

P-1428 At Databricks, we are passionate about enabling data and AI teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started. As part of the AI Platform team, you’ll build the substrate that powers everything from data apps, AI agents, model training, model serving, and vector search.  You’ll be joining a high-agency, high-visibility team operating at the frontier of AI infrastructure — with deep ties to research, product, and real-world enterprise use cases.  Databricks Mosaic AI is one of our fastest-growing businesses helping thousands of our customers democratize AI within their organizations. We’re building the infrastructure that powers the next generation of AI.  We’re hiring across multiple teams in our AI Engineering org including:   THE IMPACT YOU WILL HAVE: * Build infrastructure that powers our flagship offerings like  MLflow, AI Gateway, Databricks Apps, Agent Framework, Agent Bricks, and Foundation Model APIs, to state a few. * Improve reliability, latency, and efficiency of distributed AI workloads * Collaborate with platform, infra, and ML teams to deliver seamless end-to-end experiences * Shape how developers and data scientists build and interact with AI on Databricks WHAT WE LOOK FOR: * 5+ years of experience in backend or infrastructure engineering * Strong programming skills in Scala, Go, or Python * Experience with distributed systems, scalable APIs, or cloud-native infrastructure * Familiarity with service-oriented architecture, deployment pipelines, and system observability * Strong product and ownership mindset — you care about building the right solution, not just any solution BONUS POINTS FOR: * Experience with real-time serving, ML infrastructure, or GPU orchestration * Exposure to platforms like SageMaker, Vertex AI, or Azure ML * Contributions to OSS projects like MLflow, PyTorch, or Ray * Built developer platforms or internal tools supporting AI workflows   Pay Range Transparency Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles.  Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here.   Local Pay Range $166,000—$225,000 USD About Databricks Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook. Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here. Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.