Source-listed Job

AI Solutions Architect

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...

Job Source description available
Buckman Careers India Source published May 11, 2026 Source retrieved Oct 20, 2026
Source: Buckman Careers · A retrieval date records when our system last obtained the source record. It does not guarantee the vacancy is still open or that every detail has been independently checked.
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AI Solutions Architect opportunity at Buckman Careers
EmploymentFull Time
CountryIndia

Overview

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-

Full job description

Full Job Description

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
  1. 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
  1. 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
  1. 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
  1. 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
  1. 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

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