AI Solutions Architect

Posted 4 Days Ago
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Chennai, Tamil Nadu, IND
In-Office
Expert/Leader
Biotech
The Role
Designs and leads enterprise AI solutions across commercial, manufacturing, supply chain, and operations functions. Responsibilities include AI architecture, forecasting, optimization, data governance, Azure and Microsoft ecosystem integration, SAP connectivity, MLOps, analytics, adoption, and change management. The role drives revenue growth, supply chain efficiency, predictive decision-making, and scalable AI transformation across the organization.
Summary Generated by Built In
 AI Solutions Architect

Location: Chennai, India
Required Language: English
Employment Type: Full Time
Seniority Level: Mid-Level
Travel: 10 %
Role Overview 
We are seeking an experienced AI Solution Architect to lead the design and execution of enterprise-wide AI solutions across both Commercial and Operations functions. This role will serve as a strategic bridge between business priorities and advanced AI capabilities, driving measurable business outcomes through scalable and integrated solutions.
The role will play a critical part in shaping the organization’s AI strategy, leveraging the Microsoft ecosystem (Azure AI, Dynamics 365, Power Platform, Teams, Outlook) alongside enterprise systems such as SAP ERP, to unlock value across revenue growth, operational efficiency, and decision intelligence.
Key Responsibilities:
1. Drive Revenue Growth & Commercial Excellence
  • Design and deploy AI-driven capabilities such as: Lead prioritization models, Opportunity scoring and pipeline intelligence, Next-best-action recommendations
  • Improve sales productivity through workflow automation and intelligent insights
  • Build integrated commercial analytics across CRM, marketing, and customer datasets
  • Enable visibility into pipeline health, conversion metrics, and forecast performance
2. Strengthen Forecasting & Business Analytics
  • Develop advanced forecasting models using historical, market, and behavioural data
  • Standardize key commercial KPIs across regions and business units
  • Build scalable self-service analytics layers for business teams
  • Establish strong data governance frameworks ensuring accuracy, lineage, and transparency
3. Optimize Supply Chain & Operations
  • Implement AI-led demand planning and predictive analytics models
  • Improve inventory management through optimized policies and planning parameters
  • Develop simulation models for supply-demand and capacity planning
  • Partner with manufacturing and supply chain teams to embed predictive insights into decision-making
4. Reduce Supply Chain & Logistics Costs
  • Build optimization models for: Transportation and routing; Network design and logistics planning
  • Identify key cost drivers and efficiency opportunities in supply chain operations
  • Implement early-warning systems for disruptions and delays
  • Recommend data-driven improvements in planning cycles and network efficiency
5. Architect Enterprise AI Ecosystem
  • Define and govern enterprise-wide AI architecture across: Commercial systems (CRM, marketing tools); Operations systems (ERP, manufacturing platforms)
  • Establish robust integration patterns across ERP, CRM, and collaboration platforms
  • Design scalable, secure, and governed data pipelines
  • Standardize data models, taxonomies, and semantic layers across functions
6. Lead Adoption & Change Management
  • Drive enterprise-wide AI adoption through: Role-based training programs; Communication strategies and playbooks
  • Build and manage a network of business champions
  • Track adoption metrics, value realization, and performance impact
  • Partner with business leaders to drive process transformation and behavioural change
Key Stakeholders:
  • Growth & Innovation Teams
  • IT & Digital Functions
  • Commercial Leadership
  • Manufacturing & Supply Chain Teams
  • OpCo General Managers
  • Corporate Functions (Finance, HR)
Scope:
  • Selection of AI models, solution architecture, and analytics approaches
  • Technology stack decisions within Microsoft and Azure ecosystem
  • MLOps strategy, deployment, and release cycles
  • Prioritization of technical scalability and system improvements
  • Business case development and AI investment decisions
  • Data governance, privacy, and compliance alignment
  • KPI definition and process design with commercial and operations leaders
Qualifications & Experience: 
Education
  • Bachelor’s degree in computer science, Data Science, Engineering, or related field
  • Master’s degree preferred
Experience
  • 10–15+ years in AI/analytics, solution architecture, or enterprise data platforms
  • Proven experience in deploying AI solutions at scale in enterprise environments
  • Strong exposure to Microsoft ecosystem (Azure AI, Power Platform, Dynamics 365)
  • Experience working with ERP systems (SAP preferred)
  • Background in manufacturing, supply chain, or operations analytics is highly desirable
Technical & Functional Expertise:
  • AI/ML model development and deployment
  • Data modelling, integration frameworks, and automation
  • Commercial analytics and sales pipeline optimization
  • Supply chain analytics and optimization techniques
  • Cloud architecture (Azure) and MLOps practices

    Why This Role Matters
    :
   This role is pivotal in transforming the organization into a data-driven, AI-enabled enterprise—unlocking value across revenue growth, customer engagement, and operational excellence while establishing a scalable and         future-ready AI foundation. 

#L1-AP1

Skills Required

  • Bachelor's degree in computer science, data science, engineering, or a related field
  • Master's degree
  • 10–15+ years of experience in AI, analytics, solution architecture, or enterprise data platforms
  • Experience deploying AI solutions at scale in enterprise environments
  • Strong experience with Azure AI, Power Platform, and Dynamics 365
  • Experience working with ERP systems, preferably SAP
  • Experience in manufacturing, supply chain, or operations analytics
  • AI/ML model development and deployment expertise
  • Data modeling, integration frameworks, and automation expertise
  • Commercial analytics and sales pipeline optimization expertise
  • Supply chain analytics and optimization expertise
  • Azure cloud architecture and MLOps experience
  • English language proficiency
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The Company
HQ: Memphis, TN
1,657 Employees
Year Founded: 1945

What We Do

Buckman is completely committed to helping our customers succeed, regardless of the challenges facing them, the industry they operate in or their location in the world. To fulfill that commitment, we surround our rigorously trained industry experts with the highest-quality chemicals, the latest smart technology and advanced data analysis. All focused on helping your operation improve productivity, increase profitability, and ensure safety, compliance and sustainability. That’s more than chemistry. That’s Chemistry, connected.

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