Principal Software Automation Engineer

Make release confidence a scalable engineering capability. Own the automation strategy and evidence model that allow X3 components, upgrades, customisations and migration waves to move quickly without weakening customer continuity.

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

• Deep experience designing automation frameworks for web, API, GraphQL, data and distributed services.
• Strong programming ability in TypeScript/JavaScript, Java, Python or comparable languages, with CI/CD integration.
• Strong SQL/data validation and enterprise integration testing, including REST/SOAP, JSON/XML and batch workflows.
• Experience with containers, observability, test data, environment lifecycle, performance and reliability testing.
• Hands-on experience with containerisation and Kubernetes.
• Able to communicate a release recommendation clearly to technical and non-technical stakeholders.

Modern platform skills for this role

• Set cross-squad automated evidence for API compatibility, secure pipeline and artefact provenance, deployment/upgrade/rollback, reliability and migration reconciliation. Make quality feedback fast and actionable; use containers and Kubernetes as standard across the test platform.

Preferred skills

• Hands-on L4G/4GL or Progress 4GL, Crystal Reports, SQL Server/Oracle and data migration validation.
• Practical understanding of X3 processes, metadata, customisation and regression risk, including Web/Syracuse where applicable.
• Migration diffing, golden datasets, contract testing, property-based testing or synthetic monitoring.
• Cloud delivery, security testing and accessibility testing.
• Experience certifying partner solutions or operating quality gates across regional releases.
• Preferred, not required: prior Sage X3 experience, including Progress 4GL/L4G or proprietary/runtime-specific legacy technologies where useful for compatibility, support or migration; this is not a prerequisite for modern target-stack roles.
• Experience with comparably scaled ERP suites such as SAP, Infor, IFS, Microsoft Dynamics 365 or Oracle NetSuite, including relevant partner technologies and suites, is also desirable.
• Where relevant to the role, demonstrate end-to-end involvement in one or more ERP value streams and integrations. Breadth across manufacturing, operations, sales, HCM and finance is advantageous; experience in every domain is not required.
• ERP product and partner-suite experience is transferable evidence, not a hard gate: evaluate the candidate’s ability to learn X3 semantics, map equivalent processes and protect customer continuity rather than requiring one named vendor history.

Experience and qualifications

Typically 10+ years in software quality engineering or automation, with experience leading quality strategy across more than one team. 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

• Automated quality gates provide trusted evidence per change, release and migration wave.
• Regression coverage grows around the highest-value customer behaviour and legacy-modern equivalence risks.
• Flaky tests, escaped defects, manual verification effort and rollback uncertainty trend down.
• Every AI-generated or translated capability has human review, regression evidence, security checks and a recovery path.

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

Partners with Principal Engineers, Architects, Senior Automation and Software Engineers, Product, SRE/Cloud Support, Security, Customer Services and migration leads. Works daily with India squads and maintains overlap with Europe/North America for release decisions and incident learning.

Sage behaviours / leadership expectations

Customer Focus, Accountability, Trust, Innovation and Collaboration. Protects quality without creating theatre, makes risk legible, develops others and treats evidence as a product capability.

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.

Source and document control

Document version: 2.0.3 | Updated: 1 October 2026, 09:11 BST (UTC+01:00)

Source: Additive Roles/Principal Software Automation Engineer.docx; SHA-256 c2ee5761d46f

Change history

• 2.0.3 | 1 October 2026, 09:11 BST (UTC+01:00) | Role-specific content unchanged in this release; retained preferred ERP-suite and end-to-end domain criteria and revalidated Leela source SHA-256 lineage and en-GB proofing.

Responsibilities

Core accountabilities and decision ownership

• Define the quality and automation strategy across squads, including risk-based coverage, contract tests, regression, performance, security and operational verification.
• Own quality gates and evidence standards for AI-assisted modernisation, component releases, partner extensions and segmented migrations.
• Build or guide frameworks that make tests reliable, diagnosable, parallel and useful to engineers rather than a late manual checkpoint.
• Lead investigation of escaped defects, flaky suites, data drift and release risk; turn learning into prevention and measurable improvement.
• Mentor automation engineers and embed quality ownership in multidisciplinary squads.

Decision ownership:

Automation architecture, test evidence thresholds, quality-gate design, risk-based release recommendations and when a migration or deployment must pause, rollback or receive additional proof.

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.
• Treat Progress 4GL/L4G and X3 proprietary or runtime-specific patterns as LEGACY SOURCE technologies to understand, contain, migrate or replace. Approved target languages are modern technologies selected for the role and architecture; Java, JavaScript/TypeScript, Python, C#, Rust and Go are not labelled legacy by default.
• Demonstrate safe agentic delivery with tools such as Cursor, GitHub Copilot coding/cloud agent, Codex or Claude Code; no named product is mandatory. Show task decomposition, bounded specialist agents, scoped permissions or isolation, reviewed and tested generated changes, privacy/IP and security protection, and evidence of outcomes.
• Use harness engineering to make repositories and context legible, provide appropriate tools and guardrails, and create fast feedback and evaluation loops. Apply graph-based context, dependency or workflow techniques where useful; treat these as transferable practices, not vendor products.
• For hyperscale and sovereign cloud deployments, evaluate residency and jurisdiction, identity and control-plane separation, connectivity and operational constraints, service availability and portability, key management, observability and support, and compliance. Select patterns from workload and customer requirements, not a provider assumption.
• 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.