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Role Overview:
The Senior Assistant Treasurer plays a key role in managing and analyzing the Groups global treasury activities, with a strong and central focus on debt management, global cash flow management, procedures, and processes with a strong business orientation. This role is critical to enable accurate and valuable analysis of the companys cash flow and debt structure in a complex, multi-currency, global environment.
The role requires intensive interfaces with many functions in corporate, operations and globally with the countries' treasury/finance local teams and is expected to Act as a key deputy to the Group Treasurer.
Experience:
Global cash flow & liquidity management (cash forecasting) at least 3 years - (Must-have experience)
Debt management (loans, covenants, banks, refinancing) - (Must-have experience)
Strong collections and disbursements analysis (DSO, DIO, DPO, and working capital analysis)
Experience in global/multi-currency corporate environments
Experience working with cross-functional and international teams.

As an MLOps Team Leader, you will own our AI infrastructure and backend engineering efforts, leading a team at the intersection of systems design and machine learning to build the engineering systems that turn Deep Learning and Computer Vision research into reliable, scalable production features.

What Youll Be Doing:
Lead MLOps Engineering: Own the roadmap and execution for a team of backend and AI infrastructure/MLOps engineers, setting technical direction, removing blockers, and holding the bar on delivery quality.
Build Production AI Systems: Design and implement production-grade, end-to-end AI solutions, including agentic workflows, that integrate Deep Learning models and Computer Vision algorithms into real features. Own the offline experimentation and validation layer, including POC environments that let the Algo team move from research to production confidently.
Architect Data Platforms: Drive the design and implementation of scalable data platforms and pipelines that power our AI capabilities reliably and with an eye on cost and scale.
Cross-functional Collaboration: Work closely with the Algorithms and Data teams to tackle complex, real-world problems, translating research into shippable, maintainable systems.
Elevate Engineering Standards: Champion Software Engineering and System Design best practices across the group, introducing the right methodologies, tooling, and culture of craft.

As a Backend Team Leader, you will lead a team of backend and MLOps engineers that owns the systems behind our AI-driven product features. Your team works closest to our AI group - the Algorithms and Data teams - and owns the engineering side of turning models into reliable production capabilities.

Concretely, that means owning real backend architecture - the services and APIs that carry AI-driven capabilities into the product, the data collection pipelines that feed model training, the storage and query layers that hold model outputs and the insights we derive from them, and the validation pipelines that let us trust production flows. You will make the core design decisions on service boundaries, data models, event flows, and scale and cost tradeoffs, in a domain where both the data volume and the correctness bar are high. You do not need to arrive as an ML expert. You do need to be the kind of engineer who walks into an unfamiliar domain, learns it properly, and starts making good decisions in it.

What you'll be doing -

Lead and grow the team
Manage backend and MLOps engineers, some embedded in product pods; coach on delivery, decision-making, and career growth
Set clear expectations for ownership and quality; track progress against team goals, surfacing risks early.

Own the backend behind our AI features
Build and scale data pipelines with the AI group, and design how model insights are stored, queried, and exposed to the product
Build validation pipelines and partner with the Algo team to take models from experiment to production.

Drive architecture direction and alignment
Align backend decisions with the wider group, guide design discussions, and keep specs and plans on time
Collaborate with the platform team on infrastructure, deployment, and reliability standards.

Improve reliability and operational readiness
Raise the bar on stability, observability, and alert quality
Turn recurring issues into focused engineering work; lead debriefs and drive action items to completion.

As Backend Platform Team Leader, you'll lead the Platform pod. The pod owns our shared backend infrastructure (Kubernetes, Redpanda (Kafka), RabbitMQ, CI/CD, observability, and more), and it builds the tools, architecture and agentic workflows that let engineers in every other pod ship faster and more safely, at our growing scale

The role has two parts. As Pod Lead, you own the pod's direction, planning, delivery, and working process. As People Manager, you own the growth and performance of 3-4 direct reports, some of whom may work in other pods.

What you'll be doing -
Infrastructure Ownership: Keep our shared infrastructure reliable, secure, and cost-efficient, and make every change to it safe and well planned.
Architectural Evolution: Lead multi-quarter programs that reshape our backend, and migrate services onto them safely.
Reliability: Make sure problems surface early, and drive incidents to their real root cause.
Direction and Delivery: Maintain one clear, prioritized plan that you know in depth, and run a predictable team.
Planning and Delivery: Own sprint and quarter planning. Maintain one clear, prioritized plan that you know in depth, and run a predictable team.
Pod Process: Follow the PDLC, uphold the company's working processes and policies, and continuously shape and improve how the pod works.
Technical Ownership: Know the pod's systems and how they fit together deeply enough to reason about them with confidence, guide design decisions, and challenge assumptions.
People Leadership: Set clear goals and expectations, give honest feedback, invest in each report's growth, and stand behind your people. Where your reports work in other pods, stay aligned with those pod leads.