Senior Software Automation Engineer

Role purpose

Lead automation and quality engineering for a X3 squad, turning customer and migration risks into fast, reliable evidence that supports confident releases.

X3 context

Sage X3 is the SaaS-readiness programme for X3: a progressive transformation from tightly coupled legacy runtime patterns towards portable, cloud-operable and upgradeable capabilities. The programme protects customer behaviour, partner IP and rollback while it modernises journeys, APIs, components, data paths, business logic, delivery automation and migration economics.

The role contributes to outcome-owned squads. India is a scalable engineering and product delivery centre, connected to Europe and North America through deliberate overlap, shared standards, recorded decisions and continuous support of production outcomes.

Required technical and domain skills

• Strong automation programming in TypeScript/JavaScript, Java, Python or comparable languages.

• Experience with UI, API, GraphQL, integration, data and end-to-end test design.

• Strong SQL/data validation, REST/SOAP integration and batch or migration workflow testing.

• CI/CD, containers, test data, observability and defect analysis in a cloud-native environment.

• Hands-on experience with containerisation and Kubernetes.

• Ability to explain quality risk and evidence in clear English across time zones.

Modern platform skills for this role

• Automate contract and event-integration checks, secure pipeline controls, release/upgrade/rollback evidence, and migration reconciliation. Make failures observable and useful to developers; apply container or orchestration test environments when relevant to the suite.

Preferred skills

• Hands-on L4G/4GL or Progress 4GL, Crystal Reports, SQL Server/Oracle or Web/Syracuse testing.

• Working X3 domain knowledge and understanding of metadata, customisation and upgrade risk.

• Contract testing, performance testing, accessibility, security or chaos/resilience testing.

• Migration comparison tooling, synthetic monitoring or golden customer datasets.

• Cloud environments and partner certification.

Experience and qualifications

Typically 6+ years in quality engineering or software automation, with ownership of automation for a substantial product area. Degree or equivalent experience in computing, engineering or a related discipline.

Professional English is required for global collaboration. Equivalent practical experience is valued alongside formal qualifications.

Expected outcomes / success measures

• The squad has a trusted regression signal for the highest-risk customer and migration paths.

• Quality gates run consistently in delivery pipelines and failures are diagnosed promptly.

• Migration and upgrade evidence supports predictable go/no-go, hypercare exit and rollback decisions.

• Manual regression effort and escaped defects reduce without reducing meaningful coverage.

Measures should be agreed with the squad and reviewed through the X3 monthly scorecard and quarterly evidence gates. For this role’s owned scope, show how customer behaviour and partner investment are preserved, capabilities become portable, secure, cloud-operable and upgradeable, and quality, reliability, supportability and rollback are proven. Include safe migration and improved cost or delivery economics where relevant.

Key stakeholders and collaboration model

Works with Software Engineers, Senior/Principal Automation Engineers, Product, Architects, Cloud Support/L3, Security, Customer Services and migration/partner teams across India, Europe and North America.

Sage behaviours / leadership expectations

Customer Focus, Accountability, Trust, Innovation and Collaboration. Challenges weak evidence respectfully, follows risk to impact and helps the whole squad own quality.

Every colleague is expected to protect customer continuity, partner investment, security and the integrity of evidence. Leaders additionally create clarity, develop talent and make accountable decisions visible.

Core accountabilities and decision ownership

• Design and implement maintainable automated tests across UI, API, GraphQL, data, integration, performance and operational journeys.

• Own risk-based regression for an X3 domain or platform capability, including legacy-modern equivalence and customisation behaviour.

• Integrate tests into CI/CD quality gates and make failures diagnosable, actionable and visible to the squad.

• Support migration waves, upgrades and rollback rehearsals with repeatable evidence and clear exit criteria.

• Coach Software Automation Engineers and partner with developers early in design and implementation.

Decision ownership:

Test design and automation approach for owned scope, risk-based coverage, evidence quality and release recommendations within agreed programme guardrails.

Common capability baseline

All X3 roles are expected to build capability in the following areas. Depth and decision scope increase with level:

• Understand X3 customer workflows, metadata, customisation and architecture well enough to protect supported behaviour, partner investment and SaaS readiness in the decisions owned by the role.

• Treat the internal platform as a product: use developer and operator research, feedback and adoption evidence to reduce cognitive load; provide self-service APIs and golden paths where they solve a demonstrated need.

• Use cloud-native service boundaries, versioned API contracts and event integration where appropriate, preserving compatibility and clear ownership across X3 capabilities.

• Apply CI/CD and secure software-supply-chain controls, with identity, secrets and policy enforcement built into relevant delivery and runtime paths.

• Make services diagnosable with OpenTelemetry-compatible logs, metrics and traces; define role-appropriate SLOs, reliability and resilience evidence.

• Manage performance and cost deliberately, and engineer lifecycle, upgrade, deprecation and rollback paths as part of supported capability ownership.

• Use migration, reconciliation and compatibility evidence to preserve customer data and behaviour while moving towards portable, secure, cloud-operable and upgradeable capabilities.

• Use AI-assisted engineering securely, with human review, privacy and IP protection, regression evidence and a recovery path; use deterministic methods when they are more appropriate.

• Depth follows role scope: engineers demonstrate hands-on lifecycle capability in their discipline; managers, product and programme leaders, and architects need decision-relevant fluency, not universal coding or every tool. Containerisation and Kubernetes are required for all engineering roles. Infrastructure as code, GitOps and a custom internal developer platform apply where the role owns those paths.