Main PurposeTrafigura is seeking a senior Automation Lead to join its Trade Finance function. This is a strategic, dual-profile appointment whose primary mandate is to accelerate the team's adoption of AI, automation, and modern tooling - while maintaining operational credibility on the desk to understand workflows from the inside and drive meaningful, sustained change. The successful candidate will act as the bridge between Trade Finance operations and IT delivery teams, translating business friction into prioritised, deliverable automation initiatives, and requires a demonstrable track record as a change agent combined with sound Trade Finance domain knowledge.
Key ResponsibilitiesTechnology & Automation Leadership (approx. 60%)
- Own and maintain the Trade Finance technology and automation roadmap - identifying, prioritizing, and driving high-ROI use cases across reporting, reconciliation, controls, credit workflows, and document handling.
- Own digitalization and technology projects related to Trade Finance end-to-end - from scoping, business case, and vendor/platform evaluation through to delivery, rollout, and adoption.
- Build robust business cases for each initiative, aligned with IT architecture guidelines and the function's future-state vision.
- Partner with IT delivery teams to progress priority initiatives from concept through to production deployment, remaining engaged at every stage.
- Map and redesign business processes ahead of automation, ensuring workflows are optimized before tooling is applied.
- Prototype solutions or produce precise, IT-consumable business requirements to validate value and support production build decisions.
- Develop reusable artefacts - templates, playbooks, and requirement patterns - that accelerate future automation initiatives.
- Coach and upskill Trade Finance colleagues in modern, tool-driven ways of working, including prompt design, tool adoption, and process instrumentation.
- Serve as the visible technology advocate for the team, sharing practical outcomes and embedding a data-led, digitally native culture.
- Monitor external benchmarks from peer trading houses and Trade Finance technology providers (e.g. Komgo, Contour, Traydstream, Enigio, Bolero) and assess their applicability internally.
- Represent Trade Finance in cross-functional technology transformation forums.
- Ensure new tools and products are adopted effectively by business domains, with value measurement frameworks in place.
Trade Finance Operations (approx. 40%)
- Execute day-to-day Trade Finance responsibilities across the full instrument lifecycle, including:
- Letters of Credit: Drafting, reviewing, and ensuring compliance against UCP 600 terms; liaising with issuing banks and counterparties to satisfy collateral requirements.
- Receivable Discounting: Managing eligible receivables pools, coordinating with financing banks, and tracking utilization against approved limits.
- Borrowing Base Reporting: Compiling eligible assets and liabilities, applying advance rates and concentration limits, and preparing periodic certificates for submission to lending banks.
- Contribute to credit-limit management, collateral monitoring, and controls - flagging exceptions, escalating exposures, and ensuring bank reporting is accurate and delivered on time.
- Support Trade Finance officers during peak volume periods, audits, and monthly reporting cycles.
- Serve as an operational subject-matter expert whose hands-on experience directly informs automation priorities - identifying manual touchpoints, data gaps, and process inefficiencies that represent the highest-value opportunities on the roadmap.
Required Qualifications- 7+ years of experience combining Trade Finance or commodity finance operations with technology-driven transformation.
- Prior experience at a commodity trading house's Trade Finance or finance function with a demonstrable transformation track record, or at a Trade Finance fintech (e.g. Komgo, Contour, Traydstream, Enigio, Bolero, TradeSun, or equivalent).
- Documented automation or AI projects personally led or co-led, with quantified outcomes - including hours saved, error rate reductions, or cycle time improvements.
- Background in technology-driven business transformation: business analyst, project or programme manager, super user, or product/scrum lead.
- Experience working with leading-edge technology platforms in the Trade Finance domain.
- Working knowledge of SQL; proficiency in Python or a low-code/no-code platform (e.g. Power Apps, Retool, Alteryx, UiPath, n8n).
- Familiarity with modern AI tooling, including LLM APIs, RAG pipelines, and AI agents.
- Ability to specify integrations between trade systems (ETRM / TMS / GL / bank platforms) - integration build expertise is not required, but the ability to scope, brief, and challenge IT credibly is essential.
- Ability to interpret system architecture diagrams and data models independently.
- Comfortable prototyping with AI tools, with genuine curiosity about the application of data and AI to business processes.
- Ability to produce precise, IT-consumable requirements specifications.
- Sound understanding of Trade Finance instruments and workflows: open account, Letters of Credit, borrowing base reporting, credit exposure, collateral management, and receivable discounting.
Preferred Qualifications- Familiarity with commodity trading flows (e.g. pipeline, storage, blending, in-transit financing).
- Prior experience with next-generation ETRM platforms (e.g. Atlas, Titan).
- Background in consulting (Big 4 or MBB) with a Trade Finance or commodities focus.
- Bilingual English and Spanish.
Attributes for Success- A genuine change agent: creative, driven, and collaborative, with a strong bias towards outcomes.
- Comfortable challenging existing processes and incumbents, with the patience to bring stakeholders along and the resilience to manage pushback.
- Hands-on by instinct - focused on making things work rather than directing from a distance.
- Able to navigate ambiguity and make progress without a fully defined brief.
- Effective in cross-functional (business and IT) teams delivering complex products or projects.
- Actively models and builds a data- and AI-led culture across the wider team.
- A collaborative team player with a commitment to continuous learning.
