Senior Architect - Email & Collaboration Security

The Email & Collaboration Security (ECS) product line sits at the intersection of some of the most consequential challenges in enterprise security today: AI-augmented threats, sprawling collaboration surfaces, multi-cloud delivery complexity, and the expectation that detection and response capabilities keep pace with a threat landscape that does not wait.

This architecture is not greenfield. It carries two decades of accumulated product decisions, integration contracts, and operational constraints. The right candidate understands why that history matters before proposing how to move beyond it. Reasoning about legacy shape and evolutionary trajectory simultaneously is not optional; it is the job.

The successful candidate will serve as connective tissue across product management, engineering, and the broader Architecture Leadership Team — turning customer and business problems into coherent, deliverable technical direction, and owning the decisions that give ECS engineering teams a stable foundation to move fast with quality.

Mimecast is an AI-first engineering organisation. This is not a cultural aspiration — it is an operating expectation. The person in this role is expected to use AI tools as a genuine, daily part of how they work: for design exploration and iteration, documentation, analysis, prototyping, and research synthesis.

This means having a real, practised opinion on where AI tooling accelerates quality decisions and where it introduces risk. It also means designing systems that incorporate AI components thoughtfully: understanding the implications of LLM integration, agent boundaries, prompt and data-contract stability, and evaluation coverage for AI-driven features.

Candidates who treat AI tooling as optional or experimental are not the right fit for this role. The expectation is fluency and daily practice, not passing familiarity.

Email threat detection and prevention

Email security efficacy

Collaboration security

DMARC analyzer

Data platform and observability

Analysis and Response

End user application integration

Internal operations enablement

10+ years building and operating production SaaS systems, with at least 3 years in a Solutions Architect, Principal Engineer, or equivalent role carrying product-shaping responsibility

A genuinely broad architectural lens — thinking about system shape, data flows, and organisational constraints rather than reaching for the nearest deep technical rabbit hole

Comfort operating across cloud-native patterns (AWS, Kafka, managed services, distributed event architectures) at high throughput — able to reason about trade-offs with confidence, without needing to be the most technically specialist person in the room

Prior close collaboration with Product Managers and UX designers, with an understanding of jobs-to-be-done framing and a real opinion on what makes a product bet good — not just a technical bet

Genuine customer orientation: asking what problem the customer has before asking how to build the feature

Understanding of SaaS unit economics, the commercial implications of architectural choices, and how to reason about scale from a product perspective as well as a systems one

An understanding of what twenty years of software history means in a production system — no assumption of greenfield, and no treatment of legacy as only debt; it is accumulated context

Structure and discipline as cognitive defaults, not imposed processes — thorough, well-reasoned artefacts, and a habit of leaving things clearer than they were found

An ability to connect dots across a large picture with many moving parts, make a call, and communicate it clearly — rather than waiting for certainty that will not arrive

A proactive self-starter who identifies the right problems to work on without being told, and drives them to resolution

Comfortable acting independently within a set of principles, while keeping the right stakeholders informed and in sync — not seeking permission, but maintaining alignment

Thrives with ambiguity and treats it as a problem to be structured, not a reason to pause

Able to reach a solution even without all the knowledge in front of them — a problem-solver who knows how to navigate to an answer, not a mnemonic database

AI tooling treated as a core capability multiplier, with a real daily practice in design work, documentation, research synthesis, and prototyping

Stays ahead of where the market and the technology are going, and brings that signal back into product and architecture decisions

Background in email security, threat detection, DLP, identity, or data platforms

Familiarity with agentic AI, MCP (Model Context Protocol), or LLM application architecture

Experience with eval design for AI features, product discovery practices, or data contract / data mesh approaches

Exposure to M365 or GWS integration patterns, SMTP relay architecture, or cloud-native security SaaS

Cybersecurity is a community effort. That’s why we’re committed to building an inclusive, diverse community that celebrates and welcomes everyone – unless they’re a cybercriminal, of course.

We’re proud to be an Equal Opportunity and Affirmative Action Employer, and we’d encourage you to join us whatever your background. We particularly welcome applicants from traditionally underrepresented groups.

We consider everyone equally: your race, age, religion, sexual orientation, gender identity, ability, marital status, nationality, or any other protected characteristic won’t affect your application.

Due to certain obligations to our customers, an offer of employment will be subject to your successful completion of applicable background checks, conducted in accordance with local law.

It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment.