Quick Overview
Seniority
Mid Senior
Work mode
Hybrid
Location
United States
Posted
Yesterday
Job Description
Key Responsibilities
Analytics Strategy & Business Discovery
- Partner with business stakeholders and executive leaders to understand decision-making processes and critical business questions.
- Identify opportunities where AI can improve insight generation, decision support, and overall business outcomes.
- Translate complex business requirements into scalable analytics capabilities and AI-powered solutions.
- Define KPIs, metrics, and success measures that support digital commerce initiatives.
AI-Powered Analytics Experiences
- Design and develop agentic AI assistants that enable users to interact with business data through natural language.
- Architect Retrieval-Augmented Generation (RAG) workflows that connect AI systems to structured and unstructured data sources.
- Build semantic models that help AI systems understand business concepts, customer behaviors, products, metrics, and operational terminology.
- Continuously improve answer quality, explainability, grounding, trustworthiness, and user experience.
eCommerce Decision Intelligence
- Develop solutions supporting:
- Customer Journey Optimization
- Personalization
- Product Recommendations
- Audience Segmentation & Targeting
- Experimentation & A/B Testing
- Real-Time Decisioning
- Create executive reporting and decision-support experiences.
- Translate data-driven insights into actionable business recommendations.
AI Evaluation & Quality
- Define evaluation frameworks for analytics-focused AI applications.
- Assess solution quality, including accuracy, relevance, grounding, usability, and business impact.
- Monitor adoption, performance, cost efficiency, and operational health of AI systems.
- Establish processes for continuous improvement and quality assurance.
Platform Delivery & Collaboration
- Collaborate closely with software engineers, data scientists, analytics professionals, and business stakeholders.
- Develop reusable analytics frameworks, AI components, and best practices.
- Support deployment, ongoing optimization, and adoption of AI-powered analytics solutions.
Required Qualifications
- 7+ years of experience in AI Engineering, Analytics Engineering, Data Engineering, Software Engineering, Solution Architecture, or a related field.
- Proven experience building analytics, reporting, dashboarding, or decision-support solutions.
- Experience designing, developing, and deploying LLM-enabled applications in production environments.
- Strong understanding of semantic modeling, business metrics, and data interpretation.
- Experience with RAG architectures and agentic AI systems.
- Strong stakeholder-facing discovery, consulting, and problem-solving skills.
- Demonstrated ability to translate business questions into technical solutions.
- Strong Python development and backend engineering experience.
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