Puma Energy
Main purpose Trafigura is recruiting a hands on Forward Deployment Engineer (FDE) to sit at the intersection of product engineering and business outcomes within an assigned business domain. The FDE embeds directly with business stakeholders, leads technical deployments end to end, builds bespoke integrations and ensures the engagement layer drives measurable business value. This is not a support role: the FDE owns the full technical lifecycle, from discovery through to production, for domain specific tools, dashboards, AI assisted workflows and lightweight apps sitting on top of core enterprise systems. The role is IT owned but embedded with the business, working alongside key users and domain leads to take working prototypes through to production: integrating them with the Enterprise Data Platform and core Trafigura systems; deploying agentic AI workflows; and taking radical ownership of live production. The focus is practical delivery in the field. Key Responsibilities Customer Immersion & Solution Delivery - embed directly with assigned business teams on site to understand their workflows, constraints, and business objectives and translate prototypes into production grade applications on the agreed enterprise stack (React, Python or Node.js, PostgreSQL, AWS). Own the full technical lifecycle from discovery through to production, including architecture proposals, hardening, test coverage, performance, UX consistency, and rollout. Conduct deep dive discovery sessions, produce scoping documents, architecture decision records and reusable design system patterns across engagement layer applications. Translate technical concepts into clear business value; release frequently against a continuous backlog of business requests using ticket and feedback driven workflows. Solution Design & Implementation - architect and build production grade custom integrations, APIs, data pipelines and workflow automations between engagement layer applications and core Trafigura systems. Transform proof of concept prototypes into secure, scalable and compliant production systems - building event streams and batch interfaces that move data into governed enterprise flows, starting with read only pulls and progressing to bidirectional integration. AI & Agentic Workflows - design, deploy and orchestrate agentic AI workflows using frameworks such as LangGraph; implement RAG pipelines, fine tuned models and vector database integrations within the assigned business domain. Operate the end to end delivery toolchain (AWS, GitLab, Docker, CI/CD, infra as code) and AI assisted development environments (Claude Code and shared skills such as Shipper) so that builders and engineers can ship safely and quickly. Use AI tooling to automate diagnostics, pre analyse domain data, and reduce manual engineering lift across development, test and production environments. Governance, Security and Controls - integrate engagement layer applications with Azure Entra ID for single sign on (OIDC / SAML) and SCIM provisioning; implement industry standard user, group, role and permission models. Enforce segregation of duties, access reviews, audit logging and change management discipline appropriate for applications handling sensitive business data. Partner with IT Security, Risk and Compliance to ensure applications meet Trafigura's security and data handling standards before production rollout. Production Ownership & Troubleshooting - own deployments end to end across engagement layer applications: triage outages, perform root cause analysis, apply patches and monitor the live stack. Debug real world edge cases in live environments and resolve performance or schema conflicts under operational pressure; own runbooks, ADRs and operational handover from build to run. Take radical ownership of production issues regardless of time or complexity, coordinating with core support teams on cross system incidents. Cross Functional Collaboration - act as the day to day technical partner for the assigned business domain - visible, responsive and embedded; build trust across technical and non technical stakeholders. Partner with peer IT functions, Enterprise Architecture and Platform Engineering to align on standards and roadmap; feed reusable patterns and field insights back to the core platform team. Decompose ambiguous, open ended business problems into actionable deliverables; push back constructively when proposed approaches will not scale or will not meet control requirements. Qualifications Education & Experience - Bachelor's degree in Computer Science, Engineering or a related field. 6+ years of hands on software engineering experience, with at least 2 years embedded with users delivering production applications in financial services, commodities or comparable enterprise environments. Demonstrated experience taking proof of concept prototypes through the full technical lifecycle to secure, production grade systems; comfort owning the technical work end to end. Technical Knowledge - strong proficiency in Python and full stack engineering: React (or equivalent modern front end framework) and Node.js back end, PostgreSQL; additional languages (Go, Java) a plus. Hands on experience with cloud platforms (AWS), Docker and Kubernetes; CI/CD in GitLab (or equivalent); infra as code (e.g., Terraform); observability and monitoring stacks. Solid understanding of database systems, SQL, data modelling, ETL pipelines, REST/gRPC APIs and microservices architecture; identity and access management with OIDC / SAML and Azure Entra ID. Experience with LLMs, RAG systems, prompt engineering and AI evaluation frameworks; familiarity with MLOps, model deployment and AI observability/guardrails; working use of AI assisted development tools (e.g. Claude Code). Familiarity with one or more of: trading, ERP or treasury platforms; workflow or document platforms; or enterprise domain data models relevant to the assigned business area. Leadership & Skills - exceptional communication - able to lead a customer meeting with confidence and clarity; ships frequently, measures adoption and iterates on user feedback. Strong problem decomposition and customer empathy; comfortable operating at the business / IT boundary with domain users as well as enterprise IT peers. Radical ownership - you don't file a ticket at 2AM, you fix the problem; pragmatic judgement about what belongs on the engagement layer versus what must be solved in core enterprise systems. Clear written and verbal communication; self directed; able to prioritise independently across multiple stakeholders. Department Overview The Digital Transformation Team is a joint venture between Trading Technology and the Data Science and Engineering Team. Reporting Structure: Reports to the Team Lead, Engagement Layer Delivery within the relevant technology function, part of Business Technology Services (BTS) / IT. Skip line reporting to the Head of the relevant technology function. Embedded with the assigned business domain. The role has regular working relationships with domain leadership and users; and with peer IT functions including Enterprise Architecture and Platform Engineering. Equal Opportunity Employer We are an Equal Opportunity Employer and take pride in a diverse workforce! We do not discriminate in recruitment, hiring, training, promotion or other employment practices for reasons of race, colour, religion, gender, sexual orientation, national origin, age, marital or veteran status, medical condition or handicap, disability, or any other legally protected status.
Main purpose Trafigura is recruiting a hands on Forward Deployment Engineer (FDE) to sit at the intersection of product engineering and business outcomes within an assigned business domain. The FDE embeds directly with business stakeholders, leads technical deployments end to end, builds bespoke integrations and ensures the engagement layer drives measurable business value. This is not a support role: the FDE owns the full technical lifecycle, from discovery through to production, for domain specific tools, dashboards, AI assisted workflows and lightweight apps sitting on top of core enterprise systems. The role is IT owned but embedded with the business, working alongside key users and domain leads to take working prototypes through to production: integrating them with the Enterprise Data Platform and core Trafigura systems; deploying agentic AI workflows; and taking radical ownership of live production. The focus is practical delivery in the field. Key Responsibilities Customer Immersion & Solution Delivery - embed directly with assigned business teams on site to understand their workflows, constraints, and business objectives and translate prototypes into production grade applications on the agreed enterprise stack (React, Python or Node.js, PostgreSQL, AWS). Own the full technical lifecycle from discovery through to production, including architecture proposals, hardening, test coverage, performance, UX consistency, and rollout. Conduct deep dive discovery sessions, produce scoping documents, architecture decision records and reusable design system patterns across engagement layer applications. Translate technical concepts into clear business value; release frequently against a continuous backlog of business requests using ticket and feedback driven workflows. Solution Design & Implementation - architect and build production grade custom integrations, APIs, data pipelines and workflow automations between engagement layer applications and core Trafigura systems. Transform proof of concept prototypes into secure, scalable and compliant production systems - building event streams and batch interfaces that move data into governed enterprise flows, starting with read only pulls and progressing to bidirectional integration. AI & Agentic Workflows - design, deploy and orchestrate agentic AI workflows using frameworks such as LangGraph; implement RAG pipelines, fine tuned models and vector database integrations within the assigned business domain. Operate the end to end delivery toolchain (AWS, GitLab, Docker, CI/CD, infra as code) and AI assisted development environments (Claude Code and shared skills such as Shipper) so that builders and engineers can ship safely and quickly. Use AI tooling to automate diagnostics, pre analyse domain data, and reduce manual engineering lift across development, test and production environments. Governance, Security and Controls - integrate engagement layer applications with Azure Entra ID for single sign on (OIDC / SAML) and SCIM provisioning; implement industry standard user, group, role and permission models. Enforce segregation of duties, access reviews, audit logging and change management discipline appropriate for applications handling sensitive business data. Partner with IT Security, Risk and Compliance to ensure applications meet Trafigura's security and data handling standards before production rollout. Production Ownership & Troubleshooting - own deployments end to end across engagement layer applications: triage outages, perform root cause analysis, apply patches and monitor the live stack. Debug real world edge cases in live environments and resolve performance or schema conflicts under operational pressure; own runbooks, ADRs and operational handover from build to run. Take radical ownership of production issues regardless of time or complexity, coordinating with core support teams on cross system incidents. Cross Functional Collaboration - act as the day to day technical partner for the assigned business domain - visible, responsive and embedded; build trust across technical and non technical stakeholders. Partner with peer IT functions, Enterprise Architecture and Platform Engineering to align on standards and roadmap; feed reusable patterns and field insights back to the core platform team. Decompose ambiguous, open ended business problems into actionable deliverables; push back constructively when proposed approaches will not scale or will not meet control requirements. Qualifications Education & Experience - Bachelor's degree in Computer Science, Engineering or a related field. 6+ years of hands on software engineering experience, with at least 2 years embedded with users delivering production applications in financial services, commodities or comparable enterprise environments. Demonstrated experience taking proof of concept prototypes through the full technical lifecycle to secure, production grade systems; comfort owning the technical work end to end. Technical Knowledge - strong proficiency in Python and full stack engineering: React (or equivalent modern front end framework) and Node.js back end, PostgreSQL; additional languages (Go, Java) a plus. Hands on experience with cloud platforms (AWS), Docker and Kubernetes; CI/CD in GitLab (or equivalent); infra as code (e.g., Terraform); observability and monitoring stacks. Solid understanding of database systems, SQL, data modelling, ETL pipelines, REST/gRPC APIs and microservices architecture; identity and access management with OIDC / SAML and Azure Entra ID. Experience with LLMs, RAG systems, prompt engineering and AI evaluation frameworks; familiarity with MLOps, model deployment and AI observability/guardrails; working use of AI assisted development tools (e.g. Claude Code). Familiarity with one or more of: trading, ERP or treasury platforms; workflow or document platforms; or enterprise domain data models relevant to the assigned business area. Leadership & Skills - exceptional communication - able to lead a customer meeting with confidence and clarity; ships frequently, measures adoption and iterates on user feedback. Strong problem decomposition and customer empathy; comfortable operating at the business / IT boundary with domain users as well as enterprise IT peers. Radical ownership - you don't file a ticket at 2AM, you fix the problem; pragmatic judgement about what belongs on the engagement layer versus what must be solved in core enterprise systems. Clear written and verbal communication; self directed; able to prioritise independently across multiple stakeholders. Department Overview The Digital Transformation Team is a joint venture between Trading Technology and the Data Science and Engineering Team. Reporting Structure: Reports to the Team Lead, Engagement Layer Delivery within the relevant technology function, part of Business Technology Services (BTS) / IT. Skip line reporting to the Head of the relevant technology function. Embedded with the assigned business domain. The role has regular working relationships with domain leadership and users; and with peer IT functions including Enterprise Architecture and Platform Engineering. Equal Opportunity Employer We are an Equal Opportunity Employer and take pride in a diverse workforce! We do not discriminate in recruitment, hiring, training, promotion or other employment practices for reasons of race, colour, religion, gender, sexual orientation, national origin, age, marital or veteran status, medical condition or handicap, disability, or any other legally protected status.
Puma Energy
Trafigura is undergoing an exciting Digital Transformation, developing innovative AI technologies to change the way we work in Commodities Trading. The Document AI team is a key pillar of this initiative, unlocking data-rich proprietary documents to enable high-value process optimisation and data science use cases. We are seeking an Applied AI Engineer to grow our Document AI platform, developing robust and scalable AI solutions that solve real business problems. As a document-intensive industry, you will be building production ready Agentic AI/LLM systems that radically transform Commodities Trading. This is a hands on Individual Contributor role. Required Qualifications 5-8+ years of experience building production AI/ML systems Modern Python proficiency with deep knowledge of the ecosystem (Pydantic, FastAPI, asyncio, type safety) Experience with modern AI frameworks (we currently favour Pydantic AI) Production experience maintaining human in the loop systems and AI monitoring/observability Strong fundamentals in AI/ML evaluation frameworks Experience building agentic systems including MCP, tool calling, memory systems, vector-based knowledge stores, guardrails In depth understanding of modern software design principles (e,g. microservices, event-driven architectures, domain driven design, object oriented programming, test driven development) In depth understanding of modern software development lifecycle (CI/CD, IaC, Containerisation) Practical experience with cloud engineering (preference for AWS) Preferred Qualifications Prior experience in Commodities, Fixed Income, Equities, Asset Management is a plus Key Responsibilities Develop and maintain Python-based AI applications Build and maintain document workflows using LLMs and classical NLP Debug model performance issues, handle edge cases, and optimize system reliability Write comprehensive tests and implement monitoring for AI/ML systems Rapidly prototype new features, evaluate them, and implement to production Participate in code reviews, technical design discussions, and architecture decisions Communicate effectively with both technical and non-technical stakeholders to understand and translate business requirements into production code Example projects you might own in the first 6 months Develop a specialised agent to automate highly complex commodity trading workflow Develop an agent to operate within human workflows, including seamless UI integrations and long running durable executions Develop a new AI product to extract key insights from firmwide market intelligence emails for front and middle office Attributes for Success Engineering mindset focused on delivering practical solutions that solve real business problems Self-directed and comfortable working autonomously with minimal supervision Pragmatic approach to technology choices - you pick the right tool for the job rather than chasing trends Deep appreciation for AI system reliability - you understand that making AI systems work consistently is the hardest part of the job Intellectually curious and adaptable to rapidly evolving AI/ML landscape Strong desire to help people solve problems Key Relationships You will work closely with the Digital Transformation Team to understand business requirements and rollout production-grade applications to solve them. You will support the Data Science & Engineering teams as a Centre of Excellence for Agentic AI and related tech, providing support in the form of knowledge sharing and tool adoption. Reporting Structure You will report directly to the Document AI Lead. Equal Opportunity Employer We are an Equal Opportunity Employer and take pride in a diverse workforce. We do not discriminate in recruitment, hiring, training, promotion or other employment practices for reasons of race, colour, religion, gender, sexual orientation, national origin, age, marital or veteran status, medical condition or handicap, disability, or any other legally protected status.
Trafigura is undergoing an exciting Digital Transformation, developing innovative AI technologies to change the way we work in Commodities Trading. The Document AI team is a key pillar of this initiative, unlocking data-rich proprietary documents to enable high-value process optimisation and data science use cases. We are seeking an Applied AI Engineer to grow our Document AI platform, developing robust and scalable AI solutions that solve real business problems. As a document-intensive industry, you will be building production ready Agentic AI/LLM systems that radically transform Commodities Trading. This is a hands on Individual Contributor role. Required Qualifications 5-8+ years of experience building production AI/ML systems Modern Python proficiency with deep knowledge of the ecosystem (Pydantic, FastAPI, asyncio, type safety) Experience with modern AI frameworks (we currently favour Pydantic AI) Production experience maintaining human in the loop systems and AI monitoring/observability Strong fundamentals in AI/ML evaluation frameworks Experience building agentic systems including MCP, tool calling, memory systems, vector-based knowledge stores, guardrails In depth understanding of modern software design principles (e,g. microservices, event-driven architectures, domain driven design, object oriented programming, test driven development) In depth understanding of modern software development lifecycle (CI/CD, IaC, Containerisation) Practical experience with cloud engineering (preference for AWS) Preferred Qualifications Prior experience in Commodities, Fixed Income, Equities, Asset Management is a plus Key Responsibilities Develop and maintain Python-based AI applications Build and maintain document workflows using LLMs and classical NLP Debug model performance issues, handle edge cases, and optimize system reliability Write comprehensive tests and implement monitoring for AI/ML systems Rapidly prototype new features, evaluate them, and implement to production Participate in code reviews, technical design discussions, and architecture decisions Communicate effectively with both technical and non-technical stakeholders to understand and translate business requirements into production code Example projects you might own in the first 6 months Develop a specialised agent to automate highly complex commodity trading workflow Develop an agent to operate within human workflows, including seamless UI integrations and long running durable executions Develop a new AI product to extract key insights from firmwide market intelligence emails for front and middle office Attributes for Success Engineering mindset focused on delivering practical solutions that solve real business problems Self-directed and comfortable working autonomously with minimal supervision Pragmatic approach to technology choices - you pick the right tool for the job rather than chasing trends Deep appreciation for AI system reliability - you understand that making AI systems work consistently is the hardest part of the job Intellectually curious and adaptable to rapidly evolving AI/ML landscape Strong desire to help people solve problems Key Relationships You will work closely with the Digital Transformation Team to understand business requirements and rollout production-grade applications to solve them. You will support the Data Science & Engineering teams as a Centre of Excellence for Agentic AI and related tech, providing support in the form of knowledge sharing and tool adoption. Reporting Structure You will report directly to the Document AI Lead. Equal Opportunity Employer We are an Equal Opportunity Employer and take pride in a diverse workforce. We do not discriminate in recruitment, hiring, training, promotion or other employment practices for reasons of race, colour, religion, gender, sexual orientation, national origin, age, marital or veteran status, medical condition or handicap, disability, or any other legally protected status.