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Our client, a leading global professional services organization is looking for a Applied AI Engineering Leader for its multi-functional captive Shared Services Center (SSC) in Bengaluru, India. Our client's Technology Product Engineering has modernized software and product delivery. As clients primary internal development team It delivers innovative digital solutions to its businesses and internal operations. The team develops and deploys cutting-edge internal and go-to-market solutions. Role Overview: As a Senior Manager, Applied AI Engineering, you will set the engineering vision and technical direction for our clients enterprise solutionsmapping business capabilities to the enterprise technology landscape and defining how GenAI and agentic capabilities are built directly into the products they deliver. Leading across teams and product groups, you will stay hands-on in your craftshaping architecture, design, and codewhile driving the standards and reference architectures that engineers build against. Your leadership will be pivotal in delivering tangible value across our clients product and AI investments, aligning technical solutions with business and technology strategy, and advancing Applied AI engineering across the organization. You will bring extensive engineering craftsmanship and deep expertise across software and data engineering, solution architecture, and AI/ML and GenAI, together with an exemplary track record of high-quality, outcome-focused delivery at scale. The ideal candidate is a role-model engineering leader who leads by doingsetting vision, elevating standards, developing engineers and emerging leaders, and building trusted relationships with stakeholders from engineering teams to executives. Location: Bengaluru, India Key Responsibilities Craft and articulate a vision for Applied AI engineering across our clients enterprise solutionsmapping business capabilities to the enterprise technology landscape and defining how GenAI and agentic capabilities are built directly into the products they deliverin alignment with the business strategy and technology strategy. Collaborate with diverse stakeholders across product, engineering, experience, delivery, security, and infrastructure at all organizational levels.Advocate for, develop, and communicate the integrated Applied AI engineering, architecture, and technology strategy and its implementation roadmap to engineering teams and business stakeholders. Ensure the clients organization is well-informed about objectives, KPIs, maturity, compliance, and progress. Promote a culture of reuse, quality, and speedkeeping an eye on leverage of existing assets and on the inference, token, and cloud cost of what we build, to maximize outcomes and minimize total cost.Define, measure, and drive the achievement of KPIs and Non-Functional Requirements (NFRs) spanning system performance, scalability, security, reliability, and maintainability. Establish and evolve Applied AI engineering, architecture, and AI/ML/GenAI reference architectures, standards, and best practicesincluding spec- and context-driven development, evaluations, AI agent orchestration, and the AI and Agentic SSDLC that carries work from discovery to production to operations with full automation and quality checks through the SSDLC lifecycle. Remain hands-on with design, architecture, and codecontributing to team and product group velocity and staying engaged with engineers across the SSDLCwhile reviewing code, driving tech-debt reduction, and experimenting with new technology.As a recognized engineering leader, mentor and develop engineers and emerging engineering leaders, coaching modern Applied AI engineering practicesfull-stack and micro-services, cloud-native design, AI/ML/GenAI and agentic systems, data engineering, application-level infrastructure-as-code, and advanced deployment techniques (Blue-Green, Canary, A/B testing) that minimize downtime. Lead by example through thought leadershipshowcasing experiments internally, speaking at conferences, publishing whitepapers or blogs, and leading R&D collaborations, including with academia. Cultivate a growth mindset and modern engineering behaviors across the organization.Embrace an iterative and incremental approach to Applied AI product engineering, favoring action and rapid learning over extensive upfront planning. Apply a leaning-forward approach and empirical methods to navigate complexity and uncertainty, ensuring each iteration delivers value and stays aligned with customer and business goals.Maintain a relentless focus on solving the most critical challenges faced by customers and users, aligning technical solutions with business outcomes. Minimize unnecessary technical complexity and avoid overengineeringfeatures and functionality that do not add valueand drive teams toward peak performance through continuous learning and collaborative execution.Possess deep expertise in modern Applied AI .
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.