Staff Security Engineer - Bot & Traffic Defence

About Faire Faire is a technology wholesale platform built on the belief that the future is local. Independent retailers around the globe collectively represent a multi-hundred-billion-dollar wholesale market that has historically been fragmented and offline. At Faire, we're using the power of tech, data, and machine learning to connect this thriving community of entrepreneurs across the globe. Picture your favorite boutique in town — we help them discover the best products from around the world to sell in their stores. With the right tools and insights, we believe that we can level the playing field so businesses can grow and local communities can thrive. We’re looking for smart, resourceful and passionate people to join us as we power the shop local movement. If you believe in community, come join ours. About this role: Our Engineering organization owns the software that makes our marketplace work. Our Bot & Traffic Defence function owns how Faire holds up against automated traffic: scraping, credential abuse, and application-layer DDoS, from the edge through to detection and scoring. We care about good engineering practice and love to write software that is secure, tested, easy to maintain, and can scale to millions of users. We build scalable, reusable frameworks; consult with product teams; listen to the data; and iterate. As a Staff Security Engineer, Bot & Traffic Defence, you will be the first dedicated owner of this domain. You will set the technical direction, build the controls and signals that back it, and establish an ownership model that holds across Security, Platform, service teams, and Anti-Abuse. As a Staff Security Engineer, Bot & Traffic Defence, you’ll collaborate with us to: Own the technical strategy and roadmap for bot, scraping, and application-layer DDoS defence end to end, from edge controls through detection and scoring, including revising the strategy where the evidence contradicts it. Author and tune edge security controls as code: WAF rules, rate limiting policies, and challenge mechanisms, against real adversaries who respond to every change you make. Build higher-confidence bot and trust signals so that Faire can enforce more aggressively without turning legitimate logged-out buyers away. Design and operate distributed layer 7 rate limiting, and make the calls on keying, counter state, and where in the stack enforcement belongs. Make incident response for bot and DDoS events a solved problem: clear paging paths, runbooks a non-specialist on-call can execute at 3am, and observability that answers whether humans are actually being affected. Lead post-incident reviews on recurring classes of bot incidents so systemic causes surface instead of repeating. Build the tooling, secure defaults, and playbooks that let service-owning teams protect their own endpoints correctly without you in the loop for every decision. Land a durable ownership model across Security, Platform, service teams, and Anti-Abuse, where every attack vector has a named owner who has accepted it and it holds without escalation. Make Faire's bot posture legible to leadership, including a defensible view of residual risk, and force the outstanding business decisions that engineering is currently making by default. We’re excited about you because you have: Hands-on operational ownership of a CDN or edge security platform (Cloudflare, Akamai, Fastly, or AWS CloudFront/WAF/Shield) in production against real adversaries, managed as code rather than clicked through a vendor dashboard. Experience defending a high-traffic consumer site against scraping and application-layer DDoS, including the part where the attacker shifts vectors a week after your control ships, and the instinct to design for raising attacker cost rather than for a permanent block. A practical understanding of bot detection signals and where each one fails: TLS and HTTP fingerprinting (JA3/JA4), behavioural signals, mobile device attestation (App Attest, Play Integrity), and challenges, with a real view on the precision and recall trade-off each one carries. Experience designing distributed rate limiting at layer 7, including the differences between per-IP, per-ASN, per-session, and per-fingerprint keying, when each gets evaded, and how to hold counter state across a fleet without the limiter becoming the bottleneck. Quantitative rigour in detection work: you can measure a detection's precision and recall, set a false-positive tolerance with the business, and defend a threshold change with data rather than intuition. A preference for solving traffic and abuse problems with code rather than manual operations, including writing and maintaining internal tooling that on-call engineers depend on mid-incident. Comfort writing and reviewing code in an OOP language such as Kotlin, Java, Python, or TypeScript, enough to read an unfamiliar service, find where a control is being bypassed, and open the pull request that fixes it. Working fluency with infrastructure as code and cloud environments (Terraform, AWS or GCP, Kubernetes) sufficient to own a security control plane, and the judgment to know when a Terraform-gated workflow is too slow for an incident and needs a break-glass path with an audit trail. Experience owning incident response for a live traffic attack, including holding the authority to block traffic under time pressure. A track record of setting technical direction in an ambiguous domain with no existing owner, and of sequencing work when everything is nominally urgent. Experience landing a cross-team ownership model without authority, including moving responsibility away from a team that currently holds it and getting other teams to accept obligations they did not ask for. Comfort delivering primarily through other teams rather than personal throughput. The ability to put security risk in business terms for executives, translating traffic and abuse metrics into revenue, cost, and reputational exposure. Clear communication with engineers outside security, describing an attack and its trade-offs without alarmism or unexplained jargon. Technologies we use and teach: Kotlin, Typescript, Python Edge and CDN security tooling: WAF, rate limiting, bot management, challenge policies AWS, OCI, Terraform, Kubernetes HTTP, JSON, and Protocol Buffers Salary range: Canada: the pay range for this role is $190,500 to $262,000 per year. This role will also be eligible for equity and benefits. Actual base pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The base pay range provided is subject to change and may be modified in the future. Hybrid Faire employees currently go into the office 3 days per week on Tuesdays, Thursdays, and a third flex day of their choosing (Monday, Wednesday, or Friday). Additionally, hybrid in-office roles will have the flexibility to work remotely up to 4 weeks per year. Specific Workplace and Information Technology positions may require onsite attendance 5 days per week as will be indicated in the job posting. Why you’ll love working at Faire Move fast: You'll own meaningful problems that serve customers around the globe with the agency to move fast and see your results clearly. Equipped to scale: We invest in what matters, including the latest enterprise AI tools, to help you work smarter and get more out of every day. Best in class: Our team is full of sharp, kind, and generous colleagues who care about their craft and about helping you grow in yours. Real rewards. Competitive pay, equity, and comprehensive benefits designed to support your life inside and outside of work. Belonging: We're intentional about building an environment where every Faire employee has equal access to opportunities, growth, and success. Faire was founded in 2017 by a team of early product and engineering leads from Square. We’re backed by some of the top investors in retail and tech including: Y Combinator, L