The interesting work in enterprise security has moved inside the organization. AI agents are creating new insider risk and compliance obligations every day. Data is sprawling faster than the controls around it. At Mimecast, our product lines sit where all of that converges.
This is an architecture role reporting directly to an Enterprise Architect (EA). You’ll work alongside other Solutions Architects on the team to shape how the product evolves, how it integrates with the rest of Mimecast, and how it stays ahead of where the market is going.
The Solutions Architect role at Mimecast sits closer to the product problem. Discovery, shaping, and contract design now drive more of the value than detailed component design. If you primarily want to be a heads-down individual contributor, this isn’t the right seat. If you want to shape what gets built and own the structural decisions that make a product line move fast with quality, it is.
Mimecast is an AI-First engineering organization. We expect this role to use AI development tools daily — for design exploration, prototyping, documentation, code review, and analysis. This is not optional and it is not bolt-on; it is how we work.
You will also be designing systems that incorporate AI directly. This product line is actively building agent-aware detections and AI-driven enrichment, and contributing to Mimecast’s broader AI-powered risk products. Comfort designing with — and for — LLMs, agents, and modern AI architectures is core to this job, not a side interest.
We treat architecture artifacts — ADRs, AGENTS.md files (agent-readable repo context), and data contracts — as machine-readable context, not documentation. They’re the substrate that humans and agents both operate inside, and they capture the reasoning behind design decisions — the why, not just the what.
This is a leadership role shaping the future of Mimecast's Governance, Compliance & Insight (GCI) suite. GCI helps organizations manage data governance, retention, and compliance at scale. Our products include email & collaboration archiving, eDiscovery, compliance management, data retention, audit capabilities, and analytics, alongside our new AI-powered governance and compliance tools.
You will be the connective tissue across product management, user experience, and engineering to translate real customer problems into effective, efficient solutions. You will help the team unlock value across Mimecast’s entire portfolio to help customers navigate the human and agentic risks they face every day.
We operate with a sense of urgency. Cyber threats don't wait, and neither do we. You'll lead teams that move fast, make decisions with conviction, and deliver results. We expect leaders who thrive in this environment and inspire the same urgency in the teams around you.
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Shape problems with product partners: Contribute at the problem-framing stage, not just after requirements land. Run and facilitate workshops with product managers, engineers, UX designers, and subject matter experts to surface user needs, constraints, and opportunities. Define what “good” looks like in customer and business terms before settling on a technical shape.
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Own integration contracts as product artifacts: Help define how the product line touches the rest of the Mimecast platform. You’ll own the durable interfaces — APIs, events, and data contracts. You’ll also do the coordination work that makes integrations actually land.
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Build the architectural context engineering teams operate inside: ADRs, data contracts, and service interaction patterns. These are how architecture decisions get propagated and enforced at scale across humans and agents — they’re part of the build system, not the wiki.
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Set NFR and evaluability targets: Performance, availability, security, cost — help define the targets with real numbers. For AI features, extend that to eval coverage, agent boundary safety, and prompt/data-contract stability.
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Coordinate across teams and organizations: A lot of the impact in this role comes from getting the right people in the room, gathering stakeholder buy-in, and shepherding decisions to closure.
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Engage Enterprise Architecture bidirectionally: Bring cross-product and platform-level decisions to the EA for alignment. Pull EA-level constraints into product shaping early. Push back when standards don’t fit your situation, with a clear case.
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Estimate and monitor cost and unit economics: Provide cost projections for new architecture work; flag unexpected spend and propose remediation. Reason about cost per outcome — per protected user, per investigated incident, per inference — not just AWS spend.
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Wear a technical-architect hat when it adds value: Default mode is solution and product shaping. Drop into detailed technical design when the problem warrants it or when you’re unblocking a team — and know when to step back out. With agentic engineering practices in place, more of the detailed implementation work is carried by engineers with AI assistance.
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Propose technical debt work: Identify and prioritize debt reduction with Product Management partners.
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Architecture experience at scale: 8+ years building and operating production systems, and engaging with product early in the cycle. Time as a Solutions Architect, Principal Engineer, Tech Lead, Product Architect, Staff Engineer, or equivalent. Comfortable owning architecture across multiple teams.
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Cloud-native depth: Strong working knowledge of AWS (ECS/EKS, S3, DynamoDB, SQS/SNS, IAM, VPC), Kafka, and the ability to reason about distributed systems at high volume. You don’t need deeper AWS internals knowledge than the senior engineers — you need to reason about system shape and trade-offs.
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Contract-first integration thinking: A track record of designing clean contracts between systems and teams — async messaging, event streaming, REST/gRPC APIs, data contracts — and a clear point of view on when to reach for which.
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Product partnership: Comfortable working with PMs on problem definition, customer research synthesis, jobs-to-be-done framing, and outcome hypotheses. You have a point of view on what makes a good product bet, not just a good technical bet.
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AI-First working style: You actively use AI development tools day-to-day and have a real opinion on where they help and where they don’t. You’re comfortable designing systems that include LLMs, agents, retrieval, or related components — or you’re hungry to get there fast.
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Strong written and verbal communication: Can write a one-page ADR that lands, draft a solution brief that holds up under EA review, and lead a whiteboard session that produces a decision. Equally comfortable with engineers, PMs, and designers.
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Stakeholder navigation: Good at building consensus across teams and organizations. Comfortable with ambiguity.
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Self-direction: Driven, accountable, and able to identify the right problems to work on without being told. The team is small and senior — you’ll be expected to lead, not wait for direction.
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Bonus points: Background in security, compliance, eDiscovery, identity, observability, or data platforms. Familiarity with agentic AI, MCP (Model Context Protocol), or LLM application architecture. Experience with eval design for AI systems, product discovery practices, or data contract / data mesh approaches (e.g., ODCS).
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Impact: Your architecture decisions will shape one of Mimecast’s fastest-evolving product lines and protect data inside thousands of enterprises.
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Voice: Direct working relationship with senior architecture leadership and a real say in technology direction across the product line — and beyond, as opportunities present themselves.
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Modern stack and modern ways of working: AWS managed services, Kafka, modern Java and Kotlin services, a growing AI tooling footprint, and a team that defaults to ship-and-iterate over review-and-gate.
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Senior peers: A small architecture team where everyone is operating at a high level and trust runs deep.
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Bachelor’s degree in Computer Science or related field, or equivalent experience.
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8+ years of professional software engineering and architecture experience, with at least 2 years in a Solutions Architect, Principal Engineer, Tech Lead, Product Architect, Staff Engineer, or similar role with significant product-shaping responsibility.
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Willingness and drive to use AI development tools in a professional setting.
Belonging at Mimecast
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.
