Junior AI/ML Engineer Data Engineer

As a Junior AI/ML Engineer Data Engineer in the Retail Technology team, you will play a pivotal role in applying cutting-edge AI solutions to real-world retail challenges. Your primary responsibilities will include: - Designing and building operational dashboards using LLM APIs (e.g., Claude, GPT-4, Gemini) and data visualization tools to provide AI-driven insights for store operations, maintenance, and leadership teams. You will collaborate with business stakeholders to translate retail KPIs into automated dashboard metrics and build prompt pipelines and RAG workflows to power dashboard intelligence. - Monitoring and evaluating the performance of deployed ML/AI models against retail-specific metrics and implementing feedback loops to improve model accuracy. You will also conduct A/B testing and work with domain experts to curate retail-specific training data and validation sets. - Developing autonomous AI agents using LLM frameworks such as LangChain, LangGraph, CrewAI, or custom orchestration for tasks including CEO escalation handling, store operations automation, store maintenance scheduling, remote task optimization, and NSO coordination. You will define agent architectures, tool integrations, and escalation rules to ensure reliable and auditable outputs aligned with compliance standards. - Building and maintaining robust ETL/ELT pipelines to ingest data from various sources, working with cloud data warehouses and orchestration tools, and designing schemas optimized for analytical and ML workloads in a retail context. - Developing AI use cases tailored to retail operational functions, translating business problems into ML/AI problem statements, and supporting the rollout of AI tools to non-technical retail staff with clear documentation and training materials. Your qualifications for this role include proficiency in Python, experience with LLM APIs, prompt engineering, SQL, cloud data warehouses, data pipeline tools, dashboard/visualization tools, version control, CI/CD pipelines, and basic ML model lifecycle management. You should have 13 years of experience in data engineering, ML engineering, or a related AI/software role, preferably in a SaaS company, with exposure to retail operations and the ability to work cross-functionally with non-technical stakeholders. This role offers you the opportunity to work at the forefront of AI applied to the retail industry, with mentorship from experienced data and ML engineers, a collaborative team environment, and a growth path in a SaaS-style product culture. Join us to make a direct impact on operations serving thousands of stores and millions of customers in an inclusive and diverse workplace. As a Junior AI/ML Engineer Data Engineer in the Retail Technology team, you will play a pivotal role in applying cutting-edge AI solutions to real-world retail challenges. Your primary responsibilities will include: - Designing and building operational dashboards using LLM APIs (e.g., Claude, GPT-4, Gemini) and data visualization tools to provide AI-driven insights for store operations, maintenance, and leadership teams. You will collaborate with business stakeholders to translate retail KPIs into automated dashboard metrics and build prompt pipelines and RAG workflows to power dashboard intelligence. - Monitoring and evaluating the performance of deployed ML/AI models against retail-specific metrics and implementing feedback loops to improve model accuracy. You will also conduct A/B testing and work with domain experts to curate retail-specific training data and validation sets. - Developing autonomous AI agents using LLM frameworks such as LangChain, LangGraph, CrewAI, or custom orchestration for tasks including CEO escalation handling, store operations automation, store maintenance scheduling, remote task optimization, and NSO coordination. You will define agent architectures, tool integrations, and escalation rules to ensure reliable and auditable outputs aligned with compliance standards. - Building and maintaining robust ETL/ELT pipelines to ingest data from various sources, working with cloud data warehouses and orchestration tools, and designing schemas optimized for analytical and ML workloads in a retail context. - Developing AI use cases tailored to retail operational functions, translating business problems into ML/AI problem statements, and supporting the rollout of AI tools to non-technical retail staff with clear documentation and training materials. Your qualifications for this role include proficiency in Python, experience with LLM APIs, prompt engineering, SQL, cloud data warehouses, data pipeline tools, dashboard/visualization tools, version control, CI/CD pipelines, and basic ML model lifecycle management. You should have 13 years of experience in data engineering, ML engineering, or a related AI/software role, preferably in a SaaS company, with exposure to retail operations and the ability to work cross-functionally with non-techn