Sr Mgr. Machine Learning Engineering

Job Description: Sr. Engineering Manager, Intelligent Automations & Platforms

As the Intelligent Automation & Platform Service Leader, you will own the strategy and execution of enterprise-wide automation initiatives. You will build a centre of excellence (CoE) that designs, delivers and scales intelligent automation, spanning cloud infrastructure, application and business-process automation, RPA, and AI/ML solutions, to drive operational efficiency, cost optimisation and transformational innovation across all divisions.

About The Role

The Intelligent Automation and Platforms Practice Leader will be responsible for the following areas:

• Build and lead a multidisciplinary Automation Practice comprising automation architects, Cloud Infrastructure Automation engineers, Software Developers, RPA developers, AI/ML engineers, data engineers and process analysts.
• Provide design and architectural leadership to Practice teams to deliver scalable solutions that leverage best-in-class automation and System integration capabilities.
• Build enterprise-grade Automation platforms, Agentic AI workflows and tools to streamline and optimise workflows by automating repetitive tasks, reducing manual intervention and errors, and empowering employees to focus on strategic, creative work.
• Continuously enhance platform capabilities-templated workflows, low-code/drag-and-drop builders, API connectors, analytics dashboards and tailored solutions-to maximise efficiency, cost savings, resource utilisation and user experience.
• Partner with security, compliance and infrastructure teams to ensure platform scalability, reliability, and integration with existing systems
• Define and evangelise the Automation and AI roadmap, including success metrics (ROI, SLAs, and adoption rates), and the governance framework.
• Establish architectural standards, security/compliance guardrails and best practices for end-to-end automation.
• Oversee Automation lifecycles from ideation through design, development, testing, deployment and hyper care-leveraging both the platform and third-party tools as appropriate.
• Prioritise use cases based on complexity, value, risk and alignment to business objectives; ensure early successes to build momentum.
• Evaluate, select and manage partnerships with vendors (e.g. UiPath, Automation Anywhere), cloud providers (AWS, Azure, GCP), AI/ML frameworks and low-code platforms.
• Drive adoption of Infrastructure as Code (Terraform, Ansible), CI/CD, policy-as-code and automated security tooling.
• Partner closely with business leaders (Finance, HR, Sales, Operations) to identify process-level pain points and design end-to-end intelligent workflows.
• Lead AIOps initiatives to ingest monitoring and observability data (logs, metrics, traces) and apply ML-driven anomaly detection, root-cause analysis, and event correlation.
• Design and implement auto diagnosis & remediation pipelines that automatically detect, triage and resolve common incidents (e.g., infrastructure drifts, failed deployments).
• Automate routine processes and tasks-patch management, backups, user provisioning-and develop front-end web automations to script browser-based operational tasks.
• Enhance support effectiveness by automating ticket classification, routing, escalation workflows and integrating chatbots, ITSM platforms (e.g., ServiceNow) and monitoring tools for end-to-end visibility and faster MTTR.
• Work with Enterprise Architecture, Security, IT Operations, and Legal to ensure seamless integration, data privacy, and compliance.

• 15+ years in IT engineering roles, with 10+ years in leadership roles.
• Experience in Building and leading global engineering teams.
• Skilled in balancing delivery, quality, business acumen, data-driven decisions, and requirements.
• Strong organisational skills, influence, collaboration, and communication.
• Bias towards execution, engineering discipline, and technical expertise.
• Proven ability to build high-performing, empowered teams with a culture of ownership and growth.
• BS, MS, or PhD in Computer Science or equivalent.
• Creative thinker with strong ethical standards.
• Excellent written, verbal, and interpersonal communication skills, suitable for diverse global audiences.
• Proven achievements and experience leading through transformational phases.
• Focus on process improvement and automation.