Senior AI Software Engineer

About LFX LFX Digital is at the forefront of transforming the supply chain and retail industries through innovative digital ventures. Our mission is to drive sustainable consumption and create long-term value along the global value chain. LFX was established in 2021 as an affiliate of Li & Fung, a global supply chain solution provider with offices in 40 countries, with focus in apparels and home products. We leverage Li & Fung’s global network and operating experience to build, operate, and invest in digital companies in the global value chain. See https://lfxdigital.com/ Job Description We are actively seeking a highly motivated and skilled Senior AI Software Engineer to join our Strategic Data Unit (SDU), a specialized data function within the Group to create and manage common data, general algorithms, and data bridges to the LFX Group. You will be dedicated to shaping and managing group-level data, AI/ML algorithms, and data connections to the LFX Group. Key Responsibilities Application Development Design, build, and ship backend services and APIs that support SDU data and supply chain products.Write clean, tested, reviewable code; participate in design reviews and code reviews as a matter of routine.Build and maintain data pipelines and integrations across internal systems and external vendor/partner sources, utilizing both relational and graph databases (GraphDB) to accurately model and query complex supply chain networks.Develop internal tools and interfaces that make data and models usable by non-technical business teams.Maintenance and Operational Ownership Own deployed services: monitoring, alerting, logging, incident response, and root-cause follow-up.Debug and resolve production issues, including the unglamorous ones — data quality breaks, upstream schema changes, silent failures, and vector/graph index synchronization issues.Refactor and pay down technical debt; improve reliability, performance, and cost efficiency of existing systems.Maintain clear documentation, runbooks, and handover notes so systems remain supportable by others.Engineering Practices Manage CI/CD pipelines, containerised deployments, and environment configuration.Apply sensible security, access control, and data handling practices, particularly for vendor and client data.Contribute to shared standards, tooling, and conventions within the team.AI/ML Integration Integrate foundation models and ML components into production applications, with a heavy focus on building and optimizing Retrieval-Augmented Generation (RAG) architectures.Leverage knowledge graphs (GraphDB) alongside traditional vector search to enhance the factual grounding and contextual reasoning of our AI features.Deploy, serve, and maintain models in production, managing prompt design, evaluation, guardrails, and cost/latency; fine-tune open-source models where a task genuinely warrants it.Build and maintain pipelines using tools such as HuggingFace, LangChain, and image generation models where applicable to business needs.Assess new AI capabilities pragmatically: identify where they solve an actual business pain point, and where conventional software is the better answer. Job Requirements Bachelor's degree or above in computer science, engineering, or a related field.5+ years of professional software engineering and maintenance experience, with strong Python skills.Solid grounding in software fundamentals: API design, version control, testing, debugging, as well as deep familiarity with relational databases (SQL), graph databases (e.g., Neo4j, AWS Neptune), and vector stores.Working knowledge of containerisation and cloud deployment (Docker, Kubernetes, or equivalent); CI/CD experience.Practical familiarity with ML frameworks (PyTorch, scikit-learn) and the current generative AI ecosystem (open-source LLMs, HuggingFace, LangChain), with proven experience taking RAG applications from proof-of-concept to production.Demonstrated experience operating and maintaining production systems, not only building prototypes.Ability to communicate clearly with non-technical stakeholders and adapt as business needs shift.Fast learner, comfortable in a fast-paced environment with shifting priorities.