Sr Staff AI Engineer (AI Advisory, GenAI/AI Agents)

Blue Yonder•Dallas, TX

1d•$150,385 - $189,615•Remote

About The Position

The Sr. Staff AI Engineer is a senior leader within Blue Yonder’s Supply Chain Advisory AI team, responsible for designing, building, and operationalizing advanced AI and machine learning driven solutions that address complex, real world supply chain challenges. This role blends supply chain domain expertise with hands-on ML and GenAI agent development, to accelerate AI adoption and deliver measurable operational and financial outcomes. The role partners closely with customers, product, engineering, and advisory teams to translate business problems into scalable AI solutions. This role serves as a trusted expert who can clearly articulate value, guide implementation, and drive sustained adoption across customer environments. We are looking for strong candidates with hands-on architecture and engineering experience, building and deploying AI agents for enterprise customers within a professional services team.

Requirements

8 years of hands-on professional experience in data science, machine learning, advanced analytics, AI engineering, data engineering or software engineering within enterprise-scale environments.
Strong hands-on experience with Python, SQL, and modern data engineering practices, including buildable scalable data pipelines, ETL/ELT workflows, data integration processes, and production-grade analytics or AI/ML solutions.
Must have demonstrated experience with modern AI/GenAI capabilities, including agent-based systems, RAG architecture, prompt and context engineering, multi-agent orchestration, model fine-tuning, and LLM-based solution design.
Strong collaboration skills and ability to operate effectively in ambiguous, complex problem spaces.

Nice To Haves

Bachelor’s or Advanced Degree (Masters, PHD, etc.) in Data Science, Computer Science, Engineering, or a related field, or equivalent practical experience.
Familiarity with Snowflake Cortex, semantic layers, Cortex Analyst/Agents, or similar AI-enabled data platform capabilities is preferred.
experience with knowledge graphs, ontology-driven modeling, graph-based reasoning, and platforms such as Relational AI, Neo4j, or similar technologies to enhance AI agents, RAG workflows, contextual reasoning, explainability, and enterprise decision intelligence.
Deep supply chain domain expertise across one or more functional areas, including; planning, merchandising, allocation, replenishment, fulfillment, procurement, or returns.
Experience across at least one industry vertical; Manufacturing, Retail, or Logistics Service Providers (e.g., Automotive, High Tech, Hardlines, Softlines, Grocery).
Experience acting as a mentor or technical leader within AI or advanced analytics teams.

Responsibilities

Design, build, and deploy machine learning models across the full solution lifecycle, including data preparation, validation, deployment, and monitoring.
Architect and develop GenAI‑powered agents, including prompt and context engineering, retrieval‑augmented generation (RAG), multi‑agent orchestration, and integration with ML models and optimization solvers.
Translate complex customer business problems into AI‑driven predictions and recommendations that deliver measurable outcomes such as cost reduction, service improvement, and revenue uplift.
Lead and contribute to rapid customer POCs, experiments, and pilots, iterating solutions toward scalable, production‑ready implementations.
Work directly with customers to build trust, demonstrate explainability, and operationalize AI by embedding agents and models into daily workflows.
Guide customers through adoption and change management, supporting the transition from experimentation to sustained AI‑driven transformation.
Confidently communicate AI strategy, risks, and value to technical, business, and executive stakeholders.
Partner with engineering teams on full‑stack development, including front‑end and back‑end integration, microservices extensions, and CI/CD enablement.
Ensure AI solutions integrate effectively within enterprise platforms and the Blue Yonder ecosystem, balancing scalability, performance, and cost.
Act as a thought leader within the AI Advisory community, mentoring peers and contributing to best practices and delivery standards.
Stay current on advancements in ML, GenAI frameworks, and supply chain AI applications, applying new techniques where they provide tangible customer value.