Principal AI Engineer, Director

Job description

Closing date for applications: 04/09/2026 Location Gurugram, India Job typePermanent | Contract typeFull Time #R-00281537 Join our digital revolution in NatWest Digital X In everything we do, we work to one aim. To make digital experiences which are effortless and secure. So we organise ourselves around three principles: engineer, protect, and operate. We engineer simple solutions, we protect our customers, and we operate smarter. Job description This role is based in India and as such all normal working days must be carried out in India. Join us as a Principal AI Engineer • This is a challenging role where you’ll design and engineer innovative AI-powered solutions with the customer or user experience at their core • Using your engineering expertise, you’ll work closely with architects to shape major components of the bank’s target architecture and technology roadmap • You’ll gain valuable exposure to senior stakeholders while continuing to develop your technical expertise and leadership capability • We're offering this role at director level What you’ll do As a Principal AI Engineer, you’ll create customer value through innovative engineering solutions that are customer-focused, secure, scalable, high-performing and resilient. You’ll lead complex and strategically important initiatives, coordinating multiple teams to deliver meaningful business outcomes. We’ll look to you to align technical delivery with strategic objectives and help deliver against key performance measures published to our investors. You’ll also be: • Defining and implementing AI engineering strategy, architecture, design patterns and guardrails, making sure solutions are secure, resilient, observable and production-ready • Leading the development and scaling of AI-powered tooling and agent capabilities across the software delivery lifecycle • Enabling engineering teams to accelerate delivery, improve quality and augment human expertise through effective collaboration with AI agents • Providing technical leadership through design, development and operation of the Lending AI Agent Platform and its core services • Developing reusable AI engineering capabilities, including evaluation and benchmarking frameworks, testing approaches and model lifecycle tooling • Driving the adoption of context engineering patterns, governance controls and deployment automation to support trusted AI solutions at scale The skills you'll need You’ll bring significant experience in software engineering, software or database design and architecture, alongside a strong track record of developing software within Agile and DevOps environments. Along with an expert understanding of emerging technologies, engineering practices and industry trends, you’ll have substantial experience implementing software engineering best practice across scalability, automation, optimisation, availability and performance. You’ll also need: • A strong background in leading software development teams in a matrix structure, introducing and executing technical strategies • Significant experience of test-driven development and using automated testing frameworks, mocking and stubbing and unit testing tools • The ability to rapidly understand product and business requirements and translate them into effective technical solutions • Experience in loop engineering for AI agents, including feedback loops, verification loops, retry strategies, progress checks, guardrails, telemetry and safe termination criteria • A proven track record of designing and implementing multi-agent workflows, using frontier LLMs and orchestration patterns to balance quality, latency and cost Welcome to our Gurugram hub Spanning 437,000 sq. ft., our campus in Gurugram features two state-of-the-art towers – 1A and 2A at the Candor TechSpace in Sector 21. Key facts: • Surrounded by 28 acres • Space for 4,100 colleagues • Opened in 2010 Our tech stack Here’s just some of the technologies we use. Front end • JavaScript • ReactJS • AngularJS Back end • Python • Java • Microsoft Dynamics DevOps • AWS • GitLab • Google Cloud Platform Data • Kafka • Hadoop • PostgreSQL • Snowflake