This job is with Standard Chartered Bank, an inclusive employer and a member of myGwork – the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly.

Job Summary

• Deliver production-grade machine learning and generative AI solutions end-to-end, from business requirement and solution design through build, validation, deployment, monitoring and improvement.
• Engineer governed, observable and auditable agentic AI systems, including tool calling, retrieval and memory, sandboxed execution, policy and approval controls, tracing, telemetry and automated evaluations.
• Accelerate reliable delivery through coding agents and AI-assisted SDLC practices while ensuring responsible AI, security, model governance and measurable business outcomes.

Key Responsibilities

Operate as a senior individual contributor responsible for designing, building, deploying and improving production-grade ML, GenAI and agentic AI solutions, while providing technical guidance and mentoring to engineering colleagues.
• Translate business goals into scalable AI systems and deliver machine learning solutions across design, coding, training, testing, deployment and iteration. Apply NLP, computer vision, classification, clustering, deep learning, optimisation, supervised and unsupervised techniques, and select suitable algorithms, software, hardware and integration methods.
• Engineer the runtime and control layers around models, including tool calling, retrieval and memory, sandboxed execution, policy and approvals, tracing and telemetry, automated evaluations, audit trails, role-based access control and regulatory controls. Monitor model performance, remediate delivery and AI risks,



improve solutions after delivery, and use coding agents and AI-assisted SDLC practices to increase quality and consistency.
AI/ML solution engineering
• Design, code, train, test, deploy and iterate enterprise-scale machine learning and generative AI solutions that support predictions, recommendations, search and business growth strategies.
• Apply NLP, computer vision and machine learning techniques to structured and unstructured data, and choose suitable algorithms, software, hardware and integration methods.
End-to-end delivery and business outcomes
• Understand business requirements, translate goals into scalable AI systems and deliver committed scope to agreed schedules and quality standards.
• Establish scalable, efficient and automated processes for data analysis, model development, validation, implementation and post-delivery improvement.

Agentic AI harness engineering and production readiness
• Build governed, observable and evaluated agent workflows using tool calling, retrieval and memory, sandboxed execution, policy and approval controls, tracing, telemetry and automated evaluations.
• Carry out testing and validation to ensure systems operate reliably and satisfy quality, security, responsible AI and production-readiness standards.
Responsible AI, risk and governance
• Implement audit trails,



role-based access control, approval workflows and regulatory controls, and ensure AI/ML development and validation follow Responsible AI guidelines and standards.
• Identify and escalate delivery and AI risks, define remediation roadmaps, and use guardrails to mitigate hallucination, unsafe actions, data leakage and compliance violations.
Model performance and continuous improvement
• Monitor model and system performance after delivery, use relevant metrics to identify degradation or control gaps, and implement model improvements.
• Use coding agents and AI-assisted SDLC practices, including GitHub Copilot, Claude Code, specification-driven development and open specification workflows, to improve delivery quality and consistency.
Technical Guidance and Collaboration (for Non-People Leader roles)
• Provide technical guidance and share practical engineering knowledge to improve team delivery and solution quality.
• Coach and mentor colleagues on machine learning, agentic AI, harness engineering and AI-assisted SDLC practices.
• Collaborate across disciplines, uphold robust risk and conduct standards, exercise sound technical judgment and contribute to an inclusive, accountable engineering culture.
Technical guidance, collaboration and mentoring
• Provide technical direction, coaching and mentoring to colleagues building scalable machine learning and agentic AI solutions.
• Work collaboratively across engineering, product, design, infrastructure and interfacing programme teams, and build effective stakeholder relationships.

Motivations
• Solving complex business problems by turning stru

📌 Senior ML Engineer (Chennai)
🏢 Standard Chartered Bank
📍 Chennai