Staff Data Scientist

Role : Staff Data Scientist ( gen AI )

Location :  Dallas TX * ( Hybrid role )

Overview: Join Blue Yonder Gen AI team as a Staff Data Scientist, leading the development of intelligent agents and autonomous systems on our BY platform. You'll architect and implement sophisticated AI agents using Python that interact with our real-time data streams and machine learning models, creating intelligent decision-making systems that generate billions of autonomous actions daily. Collaborate closely with sales, product, and engineering teams to spearhead the design and implementation of cutting-edge agentic supply chain solutions. Drives technical excellence across the team, mentors junior associates, and maintains unwavering focus on customer success.

In this role you are responsible for:

• Designing, developing, and testing intelligent agents and multi-agent systems using frameworks like LangChain, AutoGen etc to solve complex Blue Yonder business problems with minimal supervision
• Architecting agent workflows, tool integrations, and reasoning systems.
• Developing autonomous agents capable of real-time decision making, plan execution, and self-correction within the BY platform ecosystem
• Creating prototypes and proofs of concept for innovative agentic features and multi-modal AI systems
• Integrating agent-based solutions into production systems with robust error handling and monitoring
• Mentoring team members on agent development frameworks, LLM integration patterns, and agentic system design principles
• Developing production-quality agent code with comprehensive testing, logging, and observability according to clean code principles and Blue Yonder standards
• Designing agents with operational excellence in mind, implementing self-healing capabilities and automated scaling to reduce manual intervention
• Empowering team members through knowledge sharing on prompt engineering, evaluations, agent orchestration, and tool-use patterns
• Leading by example in adopting cutting-edge agentic AI technologies and best practices

Technical Environment Operate within a sophisticated agentic AI landscape, utilizing Python 3.* with specialized agent frameworks including LangChain, LlamaIndex, AutoGen, and custom agent orchestration systems. Leverage core ML frameworks such as TensorFlow, PyTorch alongside LLM APIs, vector databases, and agent-specific tools. Work with BigQuery, Apache Beam, Apache Spark, Kubeflow, Dataflow, Kubernetes, Kafka, Pub/Sub, and Flask in building scalable agent infrastructure. Our agentic architecture follows event-driven, autonomous, and self-monitoring principles within a secure multi-tenant Microservices design, hosted on Azure Cloud with specialized agent runtime environments.

Responsibilities:

• Lead the team in implementing intelligent agents, autonomous decision systems, and multi-agent orchestration on the BY platform
• Design and develop sophisticated agent workflows that combine reasoning, planning, tool-use, and execution capabilities
• Collaborate with cross-functional teams to create agents for data enrichment and automated feature engineering
• Build agents capable of autonomous model evaluation, selection, and performance reporting with human oversight
• Ensure robust deployment of agent systems with comprehensive monitoring, logging, and fail-safe mechanisms
• Drive collaboration with product, sales, and engineering teams to integrate agentic capabilities into customer-facing solutions
• Develop agents that autonomously discover patterns, generate and test hypotheses, and adapt strategies based on outcomes

Qualifications:

• Bachelor's degree in Computer Science, AI/ML, or related STEM field required; advanced degree preferred
• Minimum 8 years of experience with strong foundation in data science, deep learning, and emerging expertise in agentic AI systems
• Expert-level Python programming with deep understanding of async programming, design patterns, and agent architecture principles
• Hands-on experience with agent development frameworks (LangChain, AutoGen) and LLM integration (OpenAI, Anthropic, other models)
• Proficiency with vector databases, embedding systems, and retrieval-augmented generation (RAG) architectures
• Experience with frameworks and libraries like Pandas, NumPy, Keras, TensorFlow, alongside agent-specific tools and prompt engineering
• Advanced SQL expertise and experience with real-time data processing for agent decision-making
• Experience with Big Data technologies (Snowflake, Apache Beam/Spark/Flink, Databricks) in agent-driven contexts
• Solid experience with major cloud platforms (Azure/GCP) including serverless architectures for agent deployment
• Profi