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5 days ago
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Standard Chartered·BFSI·5 days ago
5 days ago

Chennai Lead AIML Solutions

Chennai, IndiaSenior · 6-10 yearsSolutions Consultant

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Must-have skills for this role

  • agentic ai
  • solution architecture
  • engineering leadership
  • enterprise software engineering

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What you'll do

  • 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.
  • Define and execute the engineering strategy, technical direction, solution design principles and roadmap for governed agentic AI capabilities across the AI/ML delivery portfolio.
  • 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.
  • Establish standards for code quality, design reviews, documentation, peer review, automated testing, prompt and model evaluation, release controls, traceability and evidence capture.
  • Own identification, assessment, mitigation and escalation of delivery, technology, security, data, model, operational and regulatory risks.
  • Monitor adoption, performance, evaluation results, control effectiveness, incidents and business outcomes, using evidence to drive remediation and product evolution.
  • Lead, manage and develop engineering teams by setting direction, clarifying priorities, allocating work, coaching engineers and creating a high-accountability, collaborative delivery culture.

What they're looking for

  • Agentic AI solution architecture and engineering design
  • Engineering leadership, team development and delivery accountability
  • Enterprise software engineering, platform integration and AI-assisted SDLC
  • Master's degree with specialisation in Technology.

Nice to have

  • 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

Summarised by NextRaise from the employer’s description, which follows in full below.

Full description from employer

Job Description
Requisition Number:  62022
Job Location:  Chennai, IND
Global Grade:  Band 5
Work Type:  Office Working
Employment Type:  Permanent
Posting Start Date:  15/09/2026
Posting End Date:  11/10/2026
Job Description: 

Job Summary

Role Purpose

•    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.

Key Responsibilities

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 
•    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.
 

Skills and Experience

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

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 (only where mandatory): Master's degree with specialisation in Technology.
•    Language: English

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.

About Standard Chartered

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:

  • Do the right thing and are assertive, challenge one another, and live with integrity, while putting the client at the heart of what we do
  • Never settle, continuously striving to improve and innovate, keeping things simple and learning from doing well, and not so well
  • Are better together, we can be ourselves, be inclusive, see more good in others, and work collectively to build for the long term

What we offer

In line with our Fair Pay Charter, we offer a competitive salary and benefits to support your mental, physical, financial and social wellbeing.

  • Core bank funding for retirement savings, medical and life insurance, with flexible and voluntary benefits available in some locations.
  • Time-off including annual leave, parental/maternity (20 weeks), sabbatical (12 months maximum) and volunteering leave (3 days), along with minimum global standards for annual and public holiday, which is combined to 30 days minimum.
  • Flexible working options based around home and office locations, with flexible working patterns.
  • Proactive wellbeing support through Unmind, a market-leading digital wellbeing platform, development courses for resilience and other human skills, global Employee Assistance Programme, sick leave, mental health first-aiders and all sorts of self-help toolkits
  • A continuous learning culture to support your growth, with opportunities to reskill and upskill and access to physical, virtual and digital learning.
  • Being part of an inclusive and values driven organisation, one that embraces and celebrates our unique diversity, across our teams, business functions and geographies - everyone feels respected and can realise their full potential.
BFSI

Company

Standard CharteredBFSI
Chennai, India

Company facts come from this company's own listings. We only show what the postings themselves carry.

Sourced from Standard Chartered's careers site·first seen 15 Sept 2026·last verified 15 Sept 2026·How we source jobs

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