Principal Engineer

• Product and technical direction. Understand customer workflows, adoption barriers and relevant market alternatives with Product and customer-facing teams. Develop evidence-based recommendations on what to improve, simplify or avoid building. Translate agreed priorities into architecture, delivery increments and measurable outcomes.
• Hands-on delivery. Lead design, coding, review, testing and rollout of complex Java services and platform capabilities. Build critical components and reference implementations. Make trade-offs explicit and help teams deliver secure, maintainable software rather than leaving execution at the design stage.
• Production AI judgment. Develop AI-enabled capabilities where they offer meaningful customer value. Define evaluation cases, security boundaries, human approvals where needed, failure handling and acceptable cost and latency. Select conventional engineering approaches when they solve the problem more reliably.
• Reliability and modernisation. Improve performance, scalability, observability, security and tenant isolation within the assigned scope. Address technical debt through staged investments linked to customer or delivery impact. Resolve systemic causes of production problems and improve prevention.
• Cross-team influence. Align interfaces, dependencies and engineering practices across participating teams. Mentor senior engineers and explain decisions clearly. Partner with Product on priorities, Engineering Managers on delivery capacity and the Distinguished Engineer or CTO on company-wide architecture. Document decision ownership and escalate unresolved cross-product trade-offs.
• Responsibility to adhere to set internal controls.

• 12+ years delivering enterprise software, with demonstrated Principal-level ownership of significant initiatives; scope and outcomes carry more weight than tenure alone.
• Deep hands-on Java, Spring Boot, API, microservices and distributed-systems expertise.
• Strong enterprise SaaS engineering experience, including security, performance and operational reliability.
• Practical AWS or Azure architecture, containers, Kubernetes, Infrastructure as Code and CI/CD experience.
• Experience delivering AI-enabled software or developer productivity capabilities into production and evaluating their effectiveness.
• Practical familiarity with relevant AI approaches such as LLMs, RAG, agents or MCP; sound engineering judgment matters more than a particular framework.
• Evidence of influencing product decisions, leading cross-team implementation and mentoring senior contributors.
• Clear communication with technical and business stakeholders across regions.

• Salesforce metadata, APIs or release workflows; DevSecOps, CI/CD, data protection or developer-tool products.
• Modernisation of complex enterprise platforms and work in regulated or security-sensitive settings.
• Significant proprietary product achievements, open-source contributions, publications or patents demonstrating technical influence.

• Within 90 days, understand the assigned product area, agree outcome measures and identify its most consequential technical constraints.
• Within six months, deliver agreed milestones for a substantial initiative and demonstrate improvement against its baseline.
• Build durable capability in the team through reusable components, documented decisions and mentoring.

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