Senior Solution Architect

Job Summary

Math Works has a hybrid work model that enables staff members to split their time between office and home. The hybrid model provides the advantage of having both in-person time with colleagues and flexible at-home life optimizations. Learn More:

Math Works is modernizing how we design, build, and operate enterprise business applications—leveraging cloud-native architecture and an AI-first approach to delivery. We’re looking for an Architect who can span multiple architecture disciplines including Solution Architecture, Cloud Architecture, AI Architecture, and Enterprise Architecture.

This role is intentionally broad. We want a hands‑on, highly collaborative architect with a strong can‑do attitude—someone who leverages their experience, learns quickly, mentors others, and helps teams deliver secure, resilient solutions.

We use AI in two ways:

• to improve how we work (productivity and quality across the delivery lifecycle), and
• to incorporate AI capabilities into the applications we build (using a variety of models, services, and AI‑enabled SaaS features).

This role is about practical application, integration, and delivery.

Math Works nurtures growth, appreciates inclusivity, encourages initiative, values teamwork, shares success, and rewards excellence.

• Design and evolve systems using AWS cloud‑native services, aligned with the AWS Well‑Architected Framework.
• Lead solution designs across distributed systems, including integration strategies, APIs, asynchronous messaging, data flows, and hybrid/SaaS connectivity.
• Ensure security and resilience are built into the architecture from the start (secure‑by‑design patterns, least privilege, operational readiness).

• Improve resilience by contributing to risk assessments, disaster recovery plans, business continuity plans, and highly available architecture solutions.
• Partner with engineering and platform teams to improve observability, incident readiness, and operational excellence.

• Participate in and improve architecture and design reviews—focused on enabling delivery, reducing risk, and improving quality.
• Advance practical enterprise architecture capabilities: maintain visibility into the application portfolio, identify modernization opportunities, and adopt tooling that supports healthy outcomes.
• Make clear, evidence‑based recommendations on when to buy versus build solutions, and which vendor platform suites best align to specific capabilities.
• Mentor engineers and peers through collaboration, pairing, reviews, and knowledge sharing.

• Make AI a practical part of day‑to‑day delivery: accelerate discovery, design, implementation, testing, and operations using AI tooling and coding agents.
• Help teams adopt effective patterns for AI‑assisted engineering (e.g., assisted coding, test generation, debugging support, documentation and runbook improvements).
• Guide teams in using a variety of AI capabilities (models, services, and AI features in SaaS products) based on outcomes, reliability, safety, and cost.

• Design application architectures that incorporate AI capabilities in a responsible, maintainable way (e.g., intelligent search/assist, summarization, classification, workflow augmentation).
• Define practical integration patterns for AI services in enterprise applications (e.g., retrieval/knowledge augmentation, guardrails, evaluation approaches, telemetry, fallbacks).
• Partner with product owners and engineering teams to identify valuable use cases, clarify requirements, and deliver solutions that measurably improve user and business outcomes.

• Translate business goals into pragmatic architecture decisions and delivery plans.
• Provide hands‑on support where needed: prototypes, technical spikes, design iterations, and implementation guidance.
• Communicate clearly through diagrams, decision records, and concise written…