AI Solution Architect (Associate Director level)

About Company ::

Bristlecone is a supply chain and business analytics advisor, serving customers across a wide range of industries. Rated by Gartner as among the top ten system integrators in the supply chain space, we are uniquely positioned to solve contemporary business problems, with supply chain and analytics focus as our advantage. We have been a trusted partner and advisor to many leading, globally recognized companies such as Applied Materials, Exxon Mobil, Flextronics, LSI Logic, Mahindra, Motorola, Nestle, Palm, Qatar Petroleum, Ranbaxy, Unilever and Whirlpool and many others

🚀 ROLE OVERVIEW

We are seeking a visionary AI Solution Architect to lead the digital transformation of enterprise supply chains using next-generation AI. In this role, you will combine deep technical expertise in AI engineering with a strong consulting mindset. You will act as a trusted advisor, identifying high-value AI, GenAI, and Agentic AI opportunities and translating them into robust, production-ready enterprise solutions.

This role is a unique blend of strategic architecture, hands-on prototyping, and stakeholder management.

Travel on needed basis within US

⚙️ KEY RESPONSIBILITIES

• Opportunity Identification: Partner with Supply Chain process and functional experts to identify high-value AI, GenAI, and Agentic AI opportunities across Plan, Source, Make, Deliver, Warehouse, Logistics, and Aftermarket processes.
• Solution Design: Translate business requirements into AI solution designs, including agents, workflows, ML models, and decision intelligence capabilities.
• Rapid Prototyping: Rapidly develop Proof of Concepts (PoCs) and prototypes using modern AI frameworks to validate business value and technical feasibility.
• End-to-End Architecture: Define end-to-end solution architecture covering AI models, data pipelines, integrations, APIs, orchestration, security, and enterprise deployment.
• Tech Stack Evaluation: Evaluate and recommend the most appropriate AI technologies, LLMs, ML techniques, vector databases, orchestration frameworks, and cloud platforms for each use case.
• Engineering Collaboration: Collaborate with engineering teams to prepare detailed functional and technical solution specifications for production implementation.
• Asset Creation: Build reusable AI assets, accelerators, reference architectures, and Agent catalogs that can be leveraged across multiple customer engagements.
• Presales & Workshops: Support customer workshops, discovery sessions, and presales activities by presenting AI concepts, prototypes, architecture, and business value.
• Continuous Innovation: Stay current with emerging AI technologies, Agentic AI frameworks, enterprise AI platforms, and supply chain innovations to continuously enhance solution offerings.
• Trusted Advisory: Act as a trusted AI advisor by combining business process knowledge with strong AI engineering expertise to deliver innovative, scalable, and production-ready enterprise AI solutions.

📝 APPLICATION REQUIREMENT (WHAT WE LOOK FOR)

We are looking for a true builder who is deeply technical and hands-on with AI. To help us understand your background, please include a brief overview of your real-world AI experience when you apply , addressing the following:

• Project Scope & Clients: Tell us about the AI initiatives you have delivered for actual production clients. Which industries were they in, and what was the average duration of these projects?
• Technical Implementation: What specific models, algorithms, or programs did you personally build and deploy?
• Business Impact: How many of these reached full, live production, and what tangible or intangible business results did they deliver?

Your Experience Split:

Our focus is heavily weighted toward hands-on AI development rather than traditional data infrastructure. Please provide a rough percentage (%) breakdown of your recent experience:

• ____% Hands-on AI Engineering (Python coding, LLMs, frameworks like LangGraph, CrewAI, AutoGen, MCP)
• ____% Data & Enterprise Architecture (Data pipelines, cloud platforms, APIs, integrations)

🎯 IDEAL PROFILE

• Experience: 10+ years of experience in AI, Machine Learning, Data Science, or AI Solution Architecture.
• AI Tech Stack: Hands-on experience with GenAI, LLMs, Agentic AI frameworks (LangGraph, CrewAI, AutoGen, MCP/A2A), Python, cloud platforms, APIs, and enterprise solution architecture.
• Consulting Mindset: Strong consulting mindset with the ability to communicate effectively with both business stakeholders and engineering teams.
• Domain Knowledge: Experience in Supply Chain, ERP, Manufacturing, or CPG domains is highly preferred.
• Execution: Demonstrated ability to build rapid prototypes and translate ideas into enterprise-scale AI solutions.