Sr. Staff Engineer- AI (AI incubation)

Main Responsibilities

• Partner with senior leaders to identify, prioritize, and frame high-value AI opportunities tied to enterprise strategy and measurable outcomes.
• Build trusted relationships across business, product, and technology teams to strengthen the AI incubation funnel and improve cross-functional alignment.
• Translate ambiguous business problems into clear problem statements, solution hypotheses, business cases, and roadmaps.
• Orchestrate cross-functional teams across product, engineering, data, architecture, security, and platform functions from discovery through pilot and production readiness.
• Shape AI initiatives across customer, merchandising, marketing, loyalty, operations, supply chain, pharmacy, and corporate domains.
• Design enterprise-scale AI solution architectures spanning Data, ML, Foundation Models, RAG, Agentic Systems, AI Platforms, and enterprise integrations, with robust governance and production readiness.
• Establish reusable AI reference architectures, engineering standards, and solution accelerators that enable scalable, secure, and cost-effective AI adoption across the enterprise.
• Establish success metrics, experimentation plans, and adoption pathways that improve speed-to-decision and value realization.
• Accelerate initiatives from concept to pilot or production-ready design while improving the quality of governance, evaluation, and handoff into enterprise deployment.
• Provide technical leadership and mentorship across engineering, platform, and data science teams, influencing architecture and engineering decisions through deep technical expertise.
• Drive technical excellence by defining best practices for AI evaluation, observability, governance, performance, safety, and operational optimization.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, Analytics, or a related field.
• 10+ years of relevant experience in AI-led transformation, AI solutions consulting, product strategy, enterprise architecture, or related roles.
• Demonstrated ability to move from executive-level ambiguity to clear hypotheses, product prototypes, decision points, and action plans.
• Strong executive communication and stakeholder leadership skills, with the ability to influence across business, product, and technology teams.
• Demonstrated expertise designing and deploying production-scale AI systems across multiple enterprise AI layers including Machine Learning, Foundation Models, Retrieval-Augmented Generation (RAG), Agentic Systems, and AI Platforms, with Data Engineering serving as the foundational competency.
• Experience building enterprise-grade AI applications using modern AI frameworks such as LangChain, Semantic Kernel, LlamaIndex, LangGraph, or equivalent technologies.
• Demonstrated ability to establish reusable engineering patterns, technical standards, and enterprise AI best practices.
• Ability to operate effectively in fast-moving environments where priorities evolve and clarity must be created.

Preferred Background

• Experience in AI transformation, innovation, incubation, internal strategy, solutions consulting, product leadership, or enterprise architecture within large enterprises, with exposure on AI, Enterprise GenAI, AI Agents, Multi-agent systems, AI Platform Engineering, Model Evaluation, AI Governance, LLMOps, MLOps, Vector Databases & Enterprise AI Security.
• Background from top-tier consulting firms, Fortune 100-scale retailers, hyperscaler AI/solutions organizations, or high-growth AI companies.
• Familiarity with responsible AI, privacy, security, and risk considerations in enterprise or customer-facing deployments.