Note: The job is a remote job and is open to candidates in USA. Bristlecone is the industry’s largest pure-play supply chain service provider, specializing in AI-first supply chain transformations. The Data and AI Strategy Engineering Manager will lead SC Data Strategy engagements, design AI-ready architecture, and mentor consultants while driving the adoption of GenAI and Agentic AI across client operations.
Responsibilities
- Lead SC Data Strategy engagements end-to-end — from stakeholder discovery and maturity assessment through SC Data & AI architecture blueprint, implementation roadmap, governance model, and delivery plan
- AI-first framing: Engage CXO audiences on SC data strategy for AI enablement, platform investment decisions, and implementation roadmap prioritization — framing every data investment in terms of the AI outcomes it unlocks
- AI use case identification: Identify and prioritize Classical AI, GenAI and Agentic AI use cases within each client's SC program — demand sensing copilots, autonomous supply exception management, AI-powered supplier onboarding, and intelligent SC reporting
- AI-ready architecture: Design Data & AI architecture blueprints that set the foundation for Agentic AI adoption — ensuring platform choices, data product designs, feature store architectures, and governance models are AI-ready from day one
- Build and continuously enrich Bristlecone's proprietary SC data maturity benchmark database from anonymized engagement outputs — the hard-to-replicate asset that differentiates Bristlecone from other firms
- GenAI in delivery: Leverage GenAI tooling actively in your own delivery workflow — AI-assisted maturity assessment synthesis, LLM-powered roadmap generation, and AI-augmented stakeholder interview analysis to compress delivery timelines
- Conduct SC regulatory applicability assessments across CSRD, EUDR, UFLPA, and CBAM as part of the governance model deliverable
- Contribute to offering IP development — refining the assessment methodology, benchmark scoring model, and deliverable templates based on engagement experience; building AI evaluation criteria into the SC data maturity framework
- Support GTM initiatives: contribute to proposals, present at C-suite client workshops, and represent Bristlecone at key industry events as needed
- Mentor and develop SC Data Architecture Consultants and Data Governance Consultants within the Strategy & Advisory cluster — specifically on AI-augmented delivery practices
Skills
- 8-12 years of experience in supply chain, SC analytics, or SC data — with a track record spanning both strategy and execution, not advisory alone
- Prior seniority as an SC data strategist, or SC consulting manager at a Global 2000 company or consultancy
- Deep knowledge of SAP IBP/APO, Kinaxis RapidResponse, Blue Yonder, Oracle SCM Cloud — and critically, how data from each platform feeds downstream AI/ML use cases and Agentic AI workflows
- Working knowledge of cloud data and AI platform stacks: Databricks (Unity Catalog, MLflow, AI Functions), Snowflake (Cortex AI), Microsoft Fabric (Azure OpenAI integration), GCP (Vertex AI, BigQuery ML) — able to recommend the right AI-ready data stack for each client's SC context
- Practical understanding of large language models, prompt engineering, AI agents, and Agentic AI frameworks — able to have a substantive conversation with a CDO about what GenAI can and cannot reliably do in an SC context today
- Experience designing SC data governance frameworks, Data & AI implementation roadmaps, and AI readiness assessments that practitioners adopt
- Strong executive facilitation and communication skills — able to frame Data & AI investment decisions in language that resonates with CXOs
- Create thought leadership on SC AI, SC data strategy, or Agentic AI in supply chain
- Experience implementing GenAI or Agentic AI in SC contexts — demand sensing copilots, autonomous exception management agents, AI-powered supplier onboarding, or LLM-based SC reporting assistants
- Familiarity with Agentic AI frameworks: LangChain, LangGraph, Microsoft AutoGen, CrewAI, or equivalent — applied to real SC automation workflows
- Track record of building AI-ready data foundations: feature stores, vector databases, semantic data layers, or SC-specific AI model registries
- CSRD Scope 3 methodology, EUDR due diligence workflows, UFLPA audit requirements, or CBAM embedded carbon data obligations
- Published thought leadership on SC AI, SC data strategy, or Agentic AI in supply chain
Company Overview
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