Senior AI Engineer, Digital Solutions

WSP is seeking a technically credible Product Manager to lead AI product delivery across the Middle East portfolio, with the role based in the Bengaluru GCC. The position combines product ownership, technical programme leadership and stakeholder engagement. It will lead the development team, shape product roadmaps, govern delivery and ensure AI solutions move from prioritised need through secure, scalable production adoption. • Own product vision, prioritisation, roadmaps, releases, milestones and measurable delivery outcomes across multiple AI initiatives. • Lead the AI development team and coordinate engineering, data, architecture, security, product and business stakeholders. • Own technical scoping, estimation, delivery budgets, costing, dependencies, risks and governance reporting. • Translate regional business needs into clear product requirements, acceptance criteria and technically sound solution options. • Provide informed oversight of architecture, APIs, data flows, cloud-native design, AI lifecycle and production readiness. • Drive discovery, experimentation, MVP validation and evidence-based decisions on scale-up, redesign or closure. • Ensure responsible AI, cybersecurity, data protection, quality assurance and lifecycle controls are embedded in delivery. • Engage Middle East stakeholders and support client-facing discussions, demonstrations and strategic AI initiatives where required. • Create transparent performance measures covering delivery progress, adoption, quality, value and operational health. • Coach teams, remove delivery blockers and establish consistent product and engineering ways of working. • Bachelor’s degree in Computer Science, Engineering, Information Systems, Product Management or a related discipline. • 8–12 years of experience across technical product management, technical programme management, software engineering or digital product delivery. • Proven experience delivering AI, automation, analytics or platform-based products from concept to production. • Strong grounding in enterprise solution architecture, software delivery lifecycle, APIs, data models and cloud-native patterns. • Experience leading multi-disciplinary technical teams and managing senior business stakeholders. • Ability to challenge technical assumptions, make pragmatic trade-offs and communicate across executive and engineering audiences. • Experience with delivery governance, financial management, estimation, risk management, supplier or resource planning and benefits tracking. 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. 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 • Create a prioritised, transparent and outcome-led AI product portfolio aligned with Middle East business needs. • Improve predictability of delivery through clear governance, technical oversight, risk management and measurable release plans. • Enable secure transition of validated AI use cases into scalable products with clear ownership and operational readiness. • Strengthen stakeholder confidence through concise reporting, evidence-based recommendations and effective engagement. Preferred Qualification: . • PMP, PgMP, SAFe, Scrum Product Owner or equivalent product/programme certification. • Microsoft Azure, Azure AI or solution architecture certification. • Exposure to enterprise architecture frameworks and responsible AI governance. • Experience in consulting, engineering, professional services or a global GCC delivery model. 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”.