Engineering Team Lead - Email Security (Imunify Email & Email Gateway)

CloudLinux is the maker of Imunify360 — a suite of security products protecting millions of websites across the web hosting industry. Our email security line covers both sides of the email problem for hosting providers: an inbound anti-spam engine integrated with hosting control panels, and an outbound SMTP gateway that protects sender reputation and keeps legitimate mail out of the spam folder. We are looking for an Engineering Team Lead to run the team that builds and operates this product line. You will lead a small, senior, fully remote squad (currently 7–8 people: Go and Python engineers, a deliverability engineer, an anti-spam engineer, and data analysis/annotation) and be accountable for what the team ships, how reliably it runs, and how the people on it grow. This is a hands-on lead role , not a pure people-management role. Expect roughly 60% leadership (delivery, technical direction, coaching, incident command) and 40% hands-on engineering (design reviews, code review, spikes, production debugging). You are not expected to be the top individual contributor on the team — you are expected to be able to read every part of the system and hold a credible technical opinion about it. You don't need to arrive as an email expert. If you have led engineers in an adjacent technical domain — infrastructure, networking, security, messaging, anti-abuse — and have a track record of getting deep into complex technical territory fast, we will teach you the email side. The system you would inherit Inbound filtering: an Rspamd-based engine with a trained rule/ML model, released on a regular retraining cycle and measured on spam catch rate and false-positive rate. Outbound gateway: a Halon-based SMTP relay with per-domain warm-up ladders, rate limiting, quarantine, feedback-loop (ARF) processing, and a customer portal — Go services on bare metal. Panel integrations: cPanel/WHM, Plesk, DirectAdmin, plus Debian/Postfix deployments for large hosting partners. Data plane: Elasticsearch, Redis, Grafana dashboards and alerting, corpus and annotation pipelines feeding model training. Delivery: GitLab, Jenkins, Jira, weekly release cadence, blameless post-mortems within 24 hours. What you will own Delivery: Turn the product backlog into a credible, sequenced engineering plan — estimates, dependencies, and a release train the team actually hits. Run the team's weekly cadence: planning, release readiness, status reporting with real numbers rather than adjectives. Own engineering quality gates for model releases: no detection model ships without a measured catch rate and false-positive deltas against the previous model, and a rollback path. Keep technical debt visible and funded — negotiate it into the roadmap rather than absorbing it silently. Report delivery status and risk to engineering leadership weekly; every item carries an owner and a due date. Technical direction: Own the architecture of the email stack together with the architecture group: review designs, write and approve ADRs, and make build-vs-buy calls with explicit trade-offs. Review code and designs on the critical path — mail flow, rate limiting, quarantine, authentication — and set the bar for tests, observability, and safe rollout. Own production health: SLOs, alerting, capacity, and the deliverability posture of our sending infrastructure (IP reputation, SPF/DKIM/DMARC, rDNS, RBL listings). Act as incident commander for product-impacting events: coordinate remediation across teams, keep partners informed, and author the post-mortem within 24 hours with named owners and dates. People: Lead a distributed team across the globe: 1:1s, goal setting, performance reviews, and career development. Hire: define the profile, run technical interviews, onboard, and mentor engineers Set the working agreements that make async work — written decisions, public-by-default communication, durable artifacts over meetings. AI-augmented engineering: We evaluate engineers here partly on how effectively they work with coding agents. As the lead you are expected to model and coach this: prompt specificity, review quality on agent-generated code, tool-boundary awareness, context provision, iteration effectiveness, error recovery, and end-to-end task completion. The team has already scaffolded its repositories for agent-assisted development; extending that to the model and rule pipelines is live work. Working with the Product Owner: The Product Owner sets priorities, owns partner commitments and the roadmap narrative. You own the plan to deliver them and the technical risk in doing so. Escalate scope-versus-capacity conflicts early and in writing, with at least two mitigation options. First 90 days: 30 days: Own the release train and the weekly status; be able to trace an inbound message and an outbound message end to end through the stack; complete 1:1s with every team member and produce a written read on the team's strengths and gaps. 60 days: Own on-call and incident command for the product line; publish the current SLOs and the top three reliability risks with mitigations; land at least one non-trivial change yourself. 90 days: Present a technical roadmap for the email stack agreed with the PO and the architecture group, including a debt-paydown line item and a staffing recommendation. Requirements Must have: 5+ years as a software engineer, with 2+ years leading a team of engineers (team lead, tech lead with people responsibility, or engineering manager) in a product company. Strong Linux proficiency at a software engineer (user) level; comfortable reading and reviewing production code in a modern high-level programming language (Python, Go, etc.), and debugging live systems on the box. Track record of shipping and operating a distributed backend service under real production load — you have carried a pager and run incidents. Experience mastering a complex technical domain quickly and making credible architectural decisions in it. Practical fluency with observability and data tooling to judge quality yourself, not via reports (Grafana, Kibana/Elasticsearch, Redash or equivalents). Demonstrated people leadership: 1:1s, performance conversations, hiring, and growing engineers. Experience working in an agentic / AI-assisted development workflow. Understanding of ML-driven systems, including model quality evaluation, training, and production operations. Professional proficiency in English, written and spoken. Availability to work EU hours. Nice to have: Working knowledge of email infrastructure: SMTP, SPF/DKIM/DMARC, rDNS, IP reputation and warm-up, RBLs, feedback loops. Experience with open-source mail stacks — Rspamd, SpamAssassin, Postfix, Exim, Halon — or the web hosting ecosystem (cPanel/WHM and other control panels). Exposure to the ML model lifecycle: training data quality, evaluation metrics, and the trade-offs in tuning detection systems. Experience running incident and escalation management with external partners.