Software Architect

About the Role

Join the central Architects Team, a small group of senior architects partnering with every R&D department. This hands-on role spans payments, payroll, workforce management, platform, data, and security, helping teams build sound, scalable, secure systems while maintaining a coherent technical direction.

Work at the intersection of engineering, product, security, and DevOps. Dive into unfamiliar domains, influence without direct authority, and apply modern AI-assisted engineering practices to complex problems at global scale.

What You’ll Do

• Lead architectural design across multiple domains and infrastructure systems, ensuring solutions meet business, scalability, performance, and compliance needs.
• Partner with R&D, Product, Security, and DevOps teams to translate business and product requirements into clear technical direction.
• Define and maintain high-level architecture across domains, focusing on integration, maintainability, and long-term evolvability.
• Build hands-on proofs of concept to de-risk architectural decisions, validate technologies, and demonstrate viable paths before broad investment.
• Lead technical due diligence for third-party vendors, platforms, and integrations, assessing architecture fit, scalability, security, compliance, operational maturity, and long-term cost.
• Drive secure-by-design practices by embedding security, privacy, and regulatory considerations throughout system design.
• Evaluate and introduce emerging technologies, frameworks, and patterns, including AI/LLM-based capabilities where they create business value.
• Champion AI-powered engineering tools and agentic workflows across R&D, ensuring effective, safe, and consistent use.
• Define and steward architectural guidelines, standards, and best practices, and support their adoption in day-to-day delivery.
• Provide technical mentorship and architectural guidance to development teams.
• Review designs, RFCs, and critical implementations to maintain architectural consistency and quality.

Requirements

Experience & background

• 8+ years of proven experience as a System / Software Architect designing robust, scalable systems.
• 12+ years of hands-on software development experience, with strong proficiency in Java (preferred) or an equivalent backend language.
• Proven experience building enterprise SaaS platforms, self-service products, and highly scaled production systems.
• Experience in financial technology or other regulated industries is a strong advantage.
• Bachelor’s degree in Computer Science or a related technical field.

Technical depth

• Deep expertise in cloud-native architecture; AWS experience with Lambda, ECS, S3, RDS, IAM, and related services is a strong advantage.
• Hands-on experience with microservices, event-driven architectures including Kafka, RabbitMQ, and SQS, and containerized environments using Docker and Kubernetes.
• Strong command of software design patterns, SDLC, and system-integration strategies.
• Expertise in DDD, TDD, EDD, and principles including SOLID, KISS, DRY, SSOT, and CQS.
• Solid knowledge of encryption, authentication, authorization, data privacy, and secure coding practices.
• Proficiency with SQL and NoSQL databases and API design using REST and GraphQL.
• Practical experience with Git branching strategies, CI/CD pipelines, and Agile development practices.

AI-powered Engineering

• Deep hands-on experience with at least one agentic AI coding tool, such as Claude Code, Cursor, GitHub Copilot Agent Mode, or Codex CLI, used regularly on real, non-trivial work.
• Practical fluency with AI productivity tools for design and review, AI-assisted code review, documentation generation, and research.
• Ability to design effective context for AI agents through prompt writing and well-structured repositories and documentation, including CLAUDE.md or rules files.
• Familiarity with MCP and connecting AI agents to internal tools, data sources, and services.
• Awareness of security, privacy, IP, and quality risks in AI-assisted development, with approaches to organizational mitigation.
• Experience integrating AI/LLM capabilities and agent-based components into backend products and workflows is a strong plus.

Ways of Working

• Demonstrated ability to drive complex features end to end, from architecture through production.
• Excellent analytical skills and self-learning ability, with comfort ramping up quickly in unfamiliar domains.
• Strong communication and influencing skills to align engineers, product managers, and senior stakeholders around technical direction.
• Excellent written and verbal English.