Senior AI Engineer, Digital Solutions
Key Skills for This Role
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Qualifications
- Bachelor’s degree in Computer Science, Engineering or a related discipline. • 7+ years of full-stack software engineering experience, including delivery of enterprise applications to production. • Strong experience with React or Angular and backend development using Python, C#/.NET or Node.js/TypeScript. • Demonstrated experience with REST APIs, microservices, authentication, authorisation and secure coding practices. • Hands-on experience with Microsoft Azure application services, data services, Key Vault, monitoring and Azure DevOps. • Experience integrating LLM-based services, RAG or enterprise search into application workflows. • Ability to lead technical delivery, troubleshoot complex issues and communicate design decisions to technical and non-technical stakeholders.
- WSP-Aligned Technology Stack The role will use and support the approved enterprise stack below. Equivalent technologies may be considered only where formally approved through WSP architecture, security and governance processes.
- Front end React or Angular, TypeScript, HTML and CSS Back end Python, C#/.NET or Node.js/TypeScript Cloud platform Microsoft Azure AI services Azure OpenAI, Azure AI Search, Azure AI Document Intelligence, Azure Machine Learning and approved Azure AI services Application hosting Azure App Service, Azure Functions and Azure Kubernetes Service where architecturally approved Data and security Azure Storage, Azure Key Vault, SQL and approved NoSQL services Engineering lifecycle Azure DevOps, Git, CI/CD, automated testing, Azure Monitor and approved observability services Architecture REST APIs, microservices, event-driven and serverless patterns, secure API-first integration
- Expected Outcomes • Deliver secure, scalable and supportable AI-enabled applications from design through production. • Improve engineering quality through reusable architecture, automated testing, code review and observability. • Provide senior technical leadership and reduce delivery risk across the AI product portfolio.
- Preferred Qualifications • Microsoft Azure Developer, Solutions Architect or DevOps certification. • Experience with AKS, Docker, event-driven or serverless architectures. • Knowledge of AI evaluation, observability and responsible AI controls. • Experience delivering solutions in a global engineering, consulting or GCC environment.
- Ways of Working • Collaborate effectively with Middle East stakeholders, GCC delivery teams, product owners, engineering specialists and enterprise technology functions. • Work within WSP standards for architecture, cybersecurity, data protection, responsible AI, quality assurance and delivery governance. • Communicate clearly, document decisions and support transparent delivery reporting across distributed teams.
- BGV: • Employment with WSP India is subject to the successful completion of a background verification (“BGV”) check conducted by a third-party agency appointed by WSP India. • Candidates are advised to ensure that all information provided during the recruitment process — including documents uploaded — is accurate and complete, both to WSP India and its BGV partner”.
- Bachelor’s degree in Computer Science, Engineering or a related discipline.
- 7+ years of full-stack software engineering experience, including delivery of enterprise applications to production.
- Strong experience with React or Angular and backend development using Python, C#/.NET or Node.js/TypeScript.
- Demonstrated experience with REST APIs, microservices, authentication, authorisation and secure coding practices.
- Hands-on experience with Microsoft Azure application services, data services, Key Vault, monitoring and Azure DevOps.
- Experience integrating LLM-based services, RAG or enterprise search into application workflows.
- Ability to lead technical delivery, troubleshoot complex issues and communicate design decisions to technical and non-technical stakeholders.
- WSP-Aligned Technology Stack
- The role will use and support the approved enterprise stack below. Equivalent technologies may be considered only where formally approved through WSP architecture, security and governance processes.
- Expected Outcomes
- Deliver secure, scalable and supportable AI-enabled applications from design through production.
- Improve engineering quality through reusable architecture, automated testing, code review and observability.
- Provide senior technical leadership and reduce delivery risk across the AI product portfolio.
Responsibilities
- Design, develop and maintain production-grade applications across front-end and back-end layers in line with approved architecture and design standards.
- Build responsive user experiences using approved modern web frameworks and accessible design practices.
- Develop secure backend services, APIs, microservices and enterprise system connectors using approved languages and Azure services.
- Integrate Azure OpenAI, Azure AI Search and related approved AI capabilities into business applications.
- Provide technical leadership across system design, coding standards, reviews, testing, release readiness and defect resolution.
- Implement unit, integration and automated tests to reduce regression and improve application reliability.
- Contribute to CI/CD, infrastructure configuration, deployment, monitoring and post-release support using Azure DevOps.
- Work with product, QA, architecture, security and business specialists to translate requirements into maintainable solutions.
- Mentor engineers and help establish reusable patterns for enterprise AI application delivery.
Preferred Qualifications
- Microsoft Azure Developer, Solutions Architect or DevOps certification.
- Experience with AKS, Docker, event-driven or serverless architectures.
- Knowledge of AI evaluation, observability and responsible AI controls.
- Experience delivering solutions in a global engineering, consulting or GCC environment.
- Ways of Working
- Collaborate effectively with Middle East stakeholders, GCC delivery teams, product owners, engineering specialists and enterprise technology functions.
- Work within WSP standards for architecture, cybersecurity, data protection, responsible AI, quality assurance and delivery governance.
- Communicate clearly, document decisions and support transparent delivery reporting across distributed teams.
About WSP
WSP is a global professional services firm headquartered in Montréal, providing engineering, advisory, and science-based expertise. It serves clients across transportation and infrastructure, property and buildings, earth and environment, energy, water, and other sectors.
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