Job DescriptionRequired Technical SkillsC# / .
NET Core 8+ – deep understanding of the existing backend; required to assess, refactor, and migrate to modern architecturePython – modern backend development, AI/ML integration, data pipelines, automation scripting, and rapid prototyping of replacement services; required across all three rolesJavaScript / TypeScript – full-stack capability for modern service development, API layers, and Node.Js toolingJSON – schema design, API contracts, configuration-as-code, LLM function calling specifications, structured data interchangeMarkdown – documentation-as-code: ADRs, AI constitutions, specification documents, runbooksDocker / Kubernetes (EKS) – containerised deployment and orchestration; Helm charts and CI/CD pipelines (Jenkins / GitLab)Database engineering – SQL Server, Oracle RDS, and modern alternatives (PostgreSQL, columnar stores such as ClickHouse); stored procedures, query optimisation, and schema migrationData modelling & analysis – designing data schemas for the replacement platform; understanding costing WBS trees, commodities, elements, and financial factors; data quality frameworksand analytical pipelinesGitHub Copilot and Claude Code – AI-first development as the default working mode, not an optional add-onLLM integration – using AI models to replace rigid business logic with intelligent, adaptable solutionsAPI-first design – RESTful, GraphQL, and event-driven patterns for loosely-coupled architecturesAdvantageous SkillsPlatform migration / replatforming – strangler fig pattern, parallel running; experience shipping large-scale migrationsEvent streaming – Kafka, EventBridge as replacement strategies for complex Saga chainsRedis, RabbitMQ / MassTransit – understanding current patterns to inform migration strategyClickHouse or modern analytics alternatives – columnar analytics for costing and reporting dataFrontend frameworks: Angular 2+, React / Redux (awareness level is sufficient)Python data analysis libraries – pandas,



SQLAlchemy for data exploration and migration validationAI-First Cognitive RequirementsEvaluative judgment – ability to distinguish plausible AI-generated code from correct code; in high-stakes pricing logic, never self-certify money through AI aloneSpecification precision – ability to articulate precise intent, edge cases, and constraints before AI generates code; quality of specification determines everything downstreamCollaborative scepticism – working productively with AI as a collaborator you direct and challenge, not a tool you wield or an oracle you trustConstitution-building mindset – encoding failures as permanent constraints; maintaining Architecture Decision Records (ADRs) that capture why decisions were made, not just what was decidedData-first verification – the instinct that AI is only as good as the data it works from; verifying data quality at every system boundary before trusting AI outputsKey ResponsibilitiesAssess and decompose the existing 34-microservice architecture to identify simplification and replacement opportunitiesDesign and build next-generation backend services using modern Python / TypeScript stacks with LLM-augmented business logicOwn database architecture redesign – migrating from Oracle RDS / MSSQL to modern schemas (PostgreSQL, event stores) that are AI-queryable and analytics-readyBuild data quality frameworks and validation pipelines that ensure AI systems work from reliable, well-structured dataReplace rigid Saga / Orchestrator chains with AI-driven workflow engines and simpler event-driven patternsDevelop LLM-powered solutions to replace hard-coded costing rules, financial calculations,



and allocation logicOperate in the Intent → Generate → Verify → Decide → Document loop, owning decisions on irreversible, money-touching, or outward-facing logicBuild migration pathways (strangler fig, parallel running) to transition from legacy to modern architecture without service disruptionPerformance tuning and observability using Grafana, Kibana, and the ELK stackKnowledge Transfer & Key-Person Risk MitigationPair regularly with the existing DB specialist to transfer backend architecture and data modelling knowledgeDocument all schema decisions in Markdown-based ADRsRun fortnightly architecture clinics with the wider team covering Onion Architecture, DDD patterns, and database design for the new platformMaintain living runbooks so that every critical backend process can be operated or debugged by at least one other team member within 60 days of joiningContribute to CLAUDE.Md-style AI constitutions encoding pricing logic constraints and data quality rules, ensuring institutional knowledge lives in the system, not just in headsCross-train at least one frontend developer on backend API design and Python data pipelines within the first 6 monthsAt DXC Technology, we believe strong connections and community are key to our success.
Our work model prioritizes in-person collaboration while offering flexibility to support wellbeing, productivity, individual work styles, and life circumstances.
We're committed to fostering an inclusive environment where everyone can thrive.DXC Technology (NYSE: DXC) is a leading enterprise technology and innovation partner delivering software, services, and solutions to integral enterprises and public sector organizations — helping them harness AI to drive outcomes at a time of exponential change with speed.
With deep expertise in Managed Infrastructure Services, Application Modernization, and Industry-Specific Software Solutions, DXC modernizes, secures, and operates some of the world's most complex technology estates.
Learn more on dxc.Com.
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📌 Senior Platform Engineer (Xico)
🏢 DXC Technology
📍 Xico