Junior AI/ML Engineer – Data Engineer (Retail Intelligence)

Retail (Preferred: prior SaaS background)

This role bridges the gap between data infrastructure and intelligent AI-driven applications. You will work closely with retail operations, store maintenance, remote optimization (Optum), NSO (New Store Opening) teams, and senior leadership to build pipelines, AI agents, and dashboards that drive decisions at speed and scale. You will be hands-on with large language model (LLM) APIs — such as Claude, GPT-4, Gemini, or similar — to create intelligent agents and accuracy-enhanced workflows.

• Monitor and evaluate the performance of deployed ML/AI models against retail-specific metrics (accuracy, recall, F1, business KPIs).

• Implement feedback loops, fine-tuning strategies, and prompt engineering improvements to iteratively improve model accuracy.

• Conduct A/B testing and comparative evaluations of model versions.

• Work with domain experts to curate retail-specific training data and validation sets.

• Build and deploy autonomous AI agents using LLM frameworks (e.g., LangChain, LangGraph, CrewAI, AutoGen, or custom orchestration) with models such as Claude, GPT-4, or Gemini for:

– CEO Escalation Handling: Triage, summarize, and route escalated issues to the correct teams with context and recommended actions.

– Store Operations (Store Ops): Automate routine queries, anomaly alerts, and operational reporting for store managers.

– Store Maintenance: Proactive issue detection, ticket creation, and maintenance scheduling agents.

– Remote Optum: Agents that optimize staffing, remote task assignments, and operational efficiency recommendations.

– NSO (New Store Opening): End-to-end checklists, document generation, vendor coordination, and readiness tracking agents.

• Define agent architectures, tool integrations, memory strategies, and escalation rules.

• Ensure agent outputs are reliable, auditable, and aligned with compliance/retail standards.

• Build and maintain robust ETL/ELT pipelines to ingest data from POS systems, ERP platforms, IoT sensors, ticketing tools, and SaaS platforms.

• Work with cloud data warehouses (Snowflake, BigQuery, or Redshift) and orchestration tools (Airflow, dbt, Prefect).

• Ensure data quality, lineage, and governance for all pipelines feeding AI/ML systems.

• Design schemas and data models optimized for analytical and ML workloads in a retail context.

• 1–3 years of professional experience in data engineering, ML engineering, or a related AI/software role.

• Prior experience in a SaaS company is strongly preferred — you understand product thinking, iterative development, and API-driven architectures.

• Exposure to or interest in retail operations, supply chain, or brick-and-mortar technology.

• Ability to work cross-functionally with non-technical stakeholders (store managers, operations leads, C-suite).

• Experience with multi-modal AI (image/document understanding for store audits, maintenance photos, etc.).

• Exposure to agentic frameworks and tool-use patterns (function calling, MCP, etc.).

• Knowledge of retail-specific systems (SAP Retail, Oracle Retail, Manhattan Associates, etc.).

• Experience with real-time data streaming (Kafka, Kinesis).

• Prior work in building internal tooling or AI copilots for operations teams.

• Familiarity with responsible AI, bias detection, and model governance frameworks.

High-volume escalations needing fast, intelligent triage and routing

Build escalation agent with LLMs — summarize, prioritize, and route with context

Real-time ops data across 100s of stores lacking unified visibility

Data pipelines + LLM-powered dashboards and anomaly detection agents

Reactive maintenance leading to store downtime and costs

Predictive maintenance agents, auto-ticketing, and scheduling workflows

Suboptimal remote workforce task allocation and efficiency tracking

Optimization models + agent-driven task assignment recommendations

Complex, multi-team checklists and vendor coordination for new sites

NSO readiness agent — document generation, tracker, alert workflows

• Work at the cutting edge of AI applied to one of the world's largest industries — retail.

• Hands-on with LLM APIs and agentic AI architectures (Claude, GPT, Gemini, and more) from day one.

• Direct impact on operations serving thousands of stores and millions of customers.

• Mentorship from experienced data and ML engineers; fast-track growth path.

• Collaborative, cross-functional team that values curiosity, ownership, and speed.

• SaaS-style product culture in a retail-tech environment — best of both worlds.

We are an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.