Role : Staff Data Scientist ( gen AI )
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
- Proficiency with modern software development tools (Git, CI/CD pipelines, Docker, Kubernetes) adapted for agent system deployment
- Deep knowledge of LLMs, prompt engineering, tool-use patterns, multi-modal AI, and autonomous system design
- Proven experience leading technical teams and mentoring junior team members in emerging agentic AI approaches
- Desired experience with agent orchestration platforms, workflow engines, and real-time streaming architectures (Kafka, Redis, Cassandra)
- Understanding of AI safety, agent alignment, and responsible AI practices in production environments
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