Senior Solution Architect (Email & Collaboration Security)
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- 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
- ECS covers the following product and capability areas:
- 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
- Lead from Problem Space, Not Solution Space
- The role engages at the problem-framing stage, not after requirements have already hardened into tickets. This means facilitating workshops with PMs, UX, and engineers to surface real customer constraints and articulate what good looks like in business and user terms before any technical shape is proposed
- Own Integration Contracts as Product Artefacts
- The durable interfaces — APIs, event contracts, data schemas — that connect ECS capabilities to the broader Mimecast platform are first-class artefacts owned by this role. They outlast individual features, and the coordination work that makes integrations actually land across teams and time is part of the remit
- Build the Architectural Context Engineering Teams Operate Inside
- ADRs, service interaction patterns, NFR targets, and data contracts are not documentation — they are the substrate that lets engineering teams and AI-assisted development workflows make consistent decisions at scale. The artefacts produced in this role are clear, reasoned, and durable
- Govern Without Blocking
- Governance is a mechanism for alignment and acceleration, not gatekeeping. Structure and discipline are introduced where they reduce risk or improve quality — and removed where ceremony adds cost without value. The role engages the Chief Architect early, pushes back constructively when platform standards do not fit the ECS context, and helps teams close decisions with conviction rather than endless review
- Reason About Cost and Unit Economics
- Infrastructure choices are sized, cost trajectories modelled for new architecture work, and unexpected spend is flagged with a proposed remediation. The frame is cost per outcome — per protected mailbox, per remediated incident — not just monthly AWS spend
- Communicate at Every Altitude
- A one-page decision record that lands with engineers, a solution brief that holds up under senior architecture review, a strategy narrative that resonates with product and commercial leadership — this role operates across all of those registers. Whiteboard sessions produce actual decisions, not just richer ambiguity
- 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
- A genuinely broad architectural lens — thinking about system shape, data flows, and organisational constraints rather than reaching for the nearest deep technical rabbit hole
- 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
- 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
- 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
- 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
- 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
- Thrives with ambiguity and treats it as a problem to be structured, not a reason to pause
- 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
- 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
- Stays ahead of where the market and the technology are going, and brings that signal back into product and architecture decisions
- AI tooling treated as a core capability multiplier, with a real daily practice in design work, documentation, research synthesis, and prototyping
- 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