Role summary
We are seeking a highly skilled AI Engineer to design, build, and deploy production-grade AI and Generative AI solutions that power core retail capabilities across merchandising, supply chain, pricing, stores, and digital commerce. This role is deeply hands-on and focused on turning AI models into reliable, scalable, and governed products using modern data and AI platforms
Key responsibilities
AI System Design and Engineering
- Design and implement AI applications for retail scenarios such as product search, recommendations, personalization, content understanding, and customer/associate assistants (chat/voice).
- Translate high‑level product requirements into technical designs, model choices, and service interfaces that can be implemented and iterated quickly.
- Implement LLM‑ and NLP‑based solutions (e.g., retrieval‑augmented generation, document Q&A, summarization, classification) for internal knowledge assistants and customer‑facing experiences.
- Work with front‑end and back‑end engineers to embed AI capabilities into web, app, store, and internal tools, focusing on usability and performance.
Data, modeling, and evaluation
- Partner with data engineers to access and prepare data from POS, ecommerce, CRM/loyalty, product catalogs, and supply‑chain systems; design data contracts and schemas that support AI applications.
- Build and iterate on models using appropriate techniques (traditional ML, deep learning, embeddings, LLMs), balancing accuracy, robustness, and cost.
- Set up evaluation pipelines, offline metrics, and online experiments (A/B tests) to measure impact on key KPIs like conversion, engagement, attach rate, in‑stock rate, and associate productivity.
- Instrument applications with logging, tracing, and dashboards to monitor quality, latency, and errors in production.
Engineering excellence
- Develop reliable, well‑tested APIs, microservices, and jobs that run in cloud environments (AWS/Azure/GCP), using modern DevOps/CI/CD practices.
- Own the full lifecycle of features you build from design and implementation through deployment, monitoring, and iteration.
- Contribute to shared libraries, templates, and best practices that make it easier for other teams to build AI features consistently.
- Collaborate across time zones, maintaining clear communication and documentation for stakeholders.
Minimum qualifications
- Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or related technical field.
- 7+ years of experience building and deploying AI/ML‑powered applications in production, ideally in consumer, ecommerce, or retail environments.
- Strong programming skills in Python and experience with modern ML/AI frameworks (PyTorch, TensorFlow, scikit‑learn, Hugging Face, or similar).
- Experience with LLMs and NLP (prompt design, embeddings, vector databases, RAG) or strong willingness and demonstrable ability to ramp quickly.
- Hands-on experience with cloud platforms (AWS, GCP, or Azure), ML services (SageMaker, Vertex AI, Azure ML) and Databricks.
- Experience building and consuming RESTful APIs, working with SQL/NoSQL databases, and deploying services in cloud environments.
- Solid understanding of software engineering fundamentals: data structures, algorithms, testing, code reviews, and CI/CD.
- Strong communication skills and ability to collaborate with cross‑functional partners across time zones.
Nice to have
- Experience in retail, ecommerce, logistics, or similar high‑volume B2C contexts.
- Exposure to MLOps tools and concepts (feature stores, model registries, monitoring) and modern data stacks (Spark/Kafka/Airflow/dbt).
