Chennai, IN
Live, first seen by us 45 days agoSet engineering direction and architecture for agentic AI solutions
Own delivery from discovery through build, release, adoption and support
Lead and develop engineers through coaching, hiring and career planning
Embed responsible AI, model risk and data protection controls
Build reusable agentic AI patterns and AI-assisted SDLC accelerators
Set the engineering direction and translate business, risk, compliance and regulatory needs into scalable solution designs
Own execution from discovery through build, testing, release, adoption and support
Lead and develop engineers, establish standards for code quality
Embed responsible AI, model risk, data protection, access control, approval, auditability and governance controls
Create reusable engineering patterns, platforms and accelerators, including AI-assisted SDLC practices
Qualifications Key Experiences • 8-12 years of relevant hands-on experience, including engineering leadership and delivery of enterprise AI/ML or agentic AI solutions in regulated environments. Certifications / Qualifications • Master's degree with specialisation in Technology. Languages • English About Standard Chartered
From the employer’s posting.
Our purpose, to drive commerce and prosperity through our unique diversity, together with our brand promise, to be here for good are achieved by how we each live our valued behaviours.
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Yes. We’ve followed 2 other Lead AI/ML Solutions jobs there since September 2026. All 2 are still up.
New Data Leadership postings at the employers we follow are about the same over the last 6 weeks compared with the 6 before.
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We file this job under Data Leadership, by the work the posting describes.
Data leaders run data teams or design how a company's data fits together. Managers hire, set priorities and answer for whether the data work pays off; architects choose the systems and the shape of the data.
Expect years of hands-on data work, experience leading people or projects, and the ability to explain tradeoffs to executives.
Unlike a senior engineer or analyst, most of a data leader's week goes to people, planning and decisions rather than building.
The government has no code for data leaders, so these figures are for the closest group, computer and information systems managers, which includes data processing and data operations managers.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 11-3021.
• Lead people and provide end-to-end engineering accountability for governed agentic AI solutions, from discovery and architecture through delivery, production adoption, support and continuous improvement.
• Translate business, risk, compliance and regulatory needs into secure, scalable, reliable, observable and auditable AI/ML solution designs that deliver measurable business outcomes.
• Build reusable agentic AI engineering capabilities, including orchestration, tool calling, retrieval, memory, human-in-the-loop controls, sandboxed execution, automated evaluation and AI-assisted SDLC practices.
Lead a multidisciplinary engineering team and take end-to-end accountability for the strategy, architecture, delivery, governance, production adoption and continuous improvement of secure, governed and measurable agentic AI solutions.
• Set the engineering direction and translate business, risk, compliance and regulatory needs into scalable solution designs. Guide implementation of orchestration, tool calling, retrieval, memory, workflow automation, human-in-the-loop controls, sandboxed execution and enterprise integrations, while ensuring security, reliability, resilience, observability, auditability and production readiness.
• Own execution from discovery through build, testing, release, adoption and support. Lead and develop engineers, establish standards for code quality, automated testing and evaluation, manage delivery and technology risks, embed responsible AI and control requirements, engage senior stakeholders, monitor operational and business outcomes, and build reusable patterns and AI-assisted SDLC accelerators that improve quality, consistency and delivery speed.
Engineering strategy and architecture
• Define and execute the engineering strategy, technical direction, solution design principles and roadmap for governed agentic AI capabilities across the AI/ML delivery portfolio.
• Design and guide implementation of orchestration, tool calling, retrieval, memory, workflow automation, enterprise integration, human-in-the-loop controls and sandboxed execution patterns.
End-to-end delivery and business outcomes
• Own delivery from intake and discovery through design, build, test, release, production adoption, support and continuous improvement, with clear accountability for scope, quality, timelines and value.
• Partner with business, product, risk, compliance and technology stakeholders to agree priorities, outcomes, dependencies, controls and adoption requirements.
Engineering excellence and production readiness
• Establish standards for code quality, design reviews, documentation, peer review, automated testing, prompt and model evaluation, release controls, traceability and evidence capture.
• Ensure production readiness across security, reliability, scalability, resilience, observability, telemetry, support, incident response, rollback and operational handover.
Risk, responsible AI and governance
• Own identification, assessment, mitigation and escalation of delivery, technology, security, data, model, operational and regulatory risks.
• Embed responsible AI, model risk, data protection, access control, approval, auditability and governance controls, and provide evidence-based updates to decision forums.
Continuous improvement and reusable capability
• Monitor adoption, performance, evaluation results, control effectiveness, incidents and business outcomes, using evidence to drive remediation and product evolution.
• Create reusable engineering patterns, platforms and accelerators, including AI-assisted SDLC practices that improve productivity, consistency and speed without compromising control.
People and Talent (for People Leader roles only)
• Set direction and drive high performance by translating strategy into clear direction, aligning individual goals to team outcomes and providing regular, constructive feedback.
• Develop talent and capability through coaching and career conversations that build critical skills, stretch potential and prepare individuals for future opportunities.
• Lead by example by role-modelling the Bank’s valued behaviours, upholding strong risk and conduct standards, exercising sound judgment, and creating an inclusive team culture that supports wellbeing, values diverse perspectives, and drives accountability.
• Lead, manage and develop engineering teams by setting direction, clarifying priorities, allocating work, coaching engineers and creating a high-accountability, collaborative delivery culture.
• Build capability through hiring, onboarding, mentoring, career development, knowledge sharing, cross-skilling, succession planning and clear ownership of critical solutions.
Motivations
• Solving complex business, risk and regulatory problems through secure, governed and measurable AI engineering.
• Building high-performing engineering teams and reusable capabilities that improve delivery quality, speed and consistency.
• Taking solutions from ambiguity and design through reliable production adoption, then improving them using operational evidence and business outcomes.
Must-have Skills
• Agentic AI solution architecture and engineering design
• Engineering leadership, team development and delivery accountability
• Enterprise software engineering, platform integration and AI-assisted SDLC
Other Skills
• Responsible AI, model risk, data protection and control governance
• Production readiness, observability, resilience and operational support
• Senior stakeholder management, architecture governance and decision facilitation
• AI/ML delivery lifecycle, evaluation and continuous improvement
Key Experiences
• 8-12 years of relevant hands-on experience, including engineering leadership and delivery of enterprise AI/ML or agentic AI solutions in regulated environments.
Certifications / Qualifications
• Master's degree with specialisation in Technology.
Languages
• English
We're an international bank, nimble enough to act, big enough for impact. For more than 170 years, we've worked to make a positive difference for our clients, communities, and each other. We question the status quo, love a challenge and enjoy finding new opportunities to grow and do better than before. If you're looking for a career with purpose and you want to work for a bank making a difference, we want to hear from you. You can count on us to celebrate your unique talents and we can't wait to see the talents you can bring us.
Our purpose, to drive commerce and prosperity through our unique diversity, together with our brand promise, to be here for good are achieved by how we each live our valued behaviours. When you work with us, you'll see how we value difference and advocate inclusion.
Together we:
In line with our Fair Pay Charter, we offer a competitive salary and benefits to support your mental, physical, financial and social wellbeing.
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Chennai, IN
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