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.
- 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.