AI Engineer

Our client is a leading eCommerce platform serving a wide network of partner vendors and marketplaces. The goal is to leverage artificial intelligence to help partners sell more effectively — by analyzing their data, identifying opportunities, and providing real-time, actionable insights aligned with promotions and platform signals.

As an AI Engineer, you will design and build intelligent systems that turn data into insights and actions, bridging AI, data science, and engineering.

• Design and implement AI/ML pipelines to analyze partner and platform data (catalogs, traffic, promotions, segmentation, and performance).

• Identify performance gaps through root-cause analysis and uncover business or technical drivers.

• Build models for pattern detection, anomaly detection, prediction, and recommendations.

• Develop AI agents that act on business goals (e.g., suggest promotions, flag poor listings, recommend re-pricing).

• Integrate AI-driven insights into partner dashboards and promotion engines via APIs and workflows.

• Collaborate with cross-functional teams to ensure data quality and business alignment.

• Prototype and document POCs, architecture, metrics, and model behavior.

• Monitor model performance, track agent success, and continuously optimize systems.

• Communicate findings to non-technical stakeholders using clear reports or dashboards.

• Stay current with advancements in AI agents, LLMs, and orchestration frameworks.

• Bachelor’s or Master’s in Computer Science, Data Science, Machine Learning, or related field.

• 5+ years of hands-on AI/ML engineering experience (modeling, feature engineering, pipelines).

• Strong programming skills in Python (scikit-learn, TensorFlow, PyTorch, Pandas, NumPy).

• Experience working with large, multi-source datasets and robust data pipelines.

• Ability to turn business problems into analytical tasks with actionable results.

• Excellent communication skills with both technical and business audiences.

• Comfortable working in early-stage, POC-driven environments.

• Interest or experience in agentic AI and autonomous systems.

• Familiarity with MLOps and model monitoring.

• Experience with eCommerce data is a plus.

• Experience with generative AI, LLMs, RAG, or vector databases.

• Knowledge of agentic AI frameworks or multi-step agents.

• Background in recommendation systems or causal inference.

• Experience with GCP and partner-facing AI tools.

• Familiarity with A/B testing and evaluation of AI systems in production.