Staff Data Scientist

2 Months ago • 8 Years + • $140,385 PA - $165,615 PA
Data Analysis

Job Description

Join the Blue Yonder Gen AI team as a Staff Data Scientist to lead the development of intelligent agents and autonomous systems on the BY platform. You will architect and implement sophisticated AI agents using Python, interacting with real-time data streams and machine learning models to create intelligent decision-making systems. This role involves designing, developing, and testing intelligent agents and multi-agent systems, architecting agent workflows, and developing autonomous agents capable of real-time decision-making and self-correction. You will also mentor junior associates and drive technical excellence in cutting-edge agentic supply chain solutions.
Good To Have:
  • Agent orchestration platforms
  • Workflow engines
  • Real-time streaming architectures (Kafka, Redis, Cassandra)
Must Have:
  • Design, develop, and test intelligent agents and multi-agent systems using frameworks like LangChain, AutoGen.
  • Architect agent workflows, tool integrations, and reasoning systems.
  • Develop autonomous agents capable of real-time decision making, plan execution, and self-correction.
  • Create prototypes and proofs of concept for innovative agentic features and multi-modal AI systems.
  • Integrate agent-based solutions into production systems with robust error handling and monitoring.
  • Mentor team members on agent development frameworks, LLM integration patterns, and agentic system design principles.
  • Develop production-quality agent code with comprehensive testing, logging, and observability.
  • Design agents with operational excellence in mind, implementing self-healing capabilities and automated scaling.
  • Empower team members through knowledge sharing on prompt engineering, evaluations, agent orchestration, and tool-use patterns.
  • Lead by example in adopting cutting-edge agentic AI technologies and best practices.
  • Lead the team in implementing intelligent agents, autonomous decision systems, and multi-agent orchestration.
  • 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.
Perks:
  • Comprehensive Medical, Dental and Vision
  • 401K with Matching
  • Flexible Time Off
  • Corporate Fitness Program
  • Voluntary benefits such as Legal Plans, Accident and Hospital Indemnity, Pet Insurance

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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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