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.
AI Solutions Architect
Location: Chennai, India
Location: Chennai, India
Required Language: English
Employment Type: Full Time
Seniority Level: Mid-Level
Travel: 10 %
Role Overview
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
#L1-AP1
Similar Jobs
Information Technology • Business Intelligence • Consulting
Designs complex client solutions across cloud and on-premises environments. Responsibilities include gathering requirements, evaluating architectures for cost, performance, and scalability, creating technical specifications and roadmaps, developing proofs of concept, integrating multi-vendor systems, supporting implementation changes, and continuously improving designs. The role also involves client consulting, technology trend monitoring, internal knowledge sharing, and contributing to go-to-market services.
Top Skills:
Agile DevelopmentCloud ComputingEnterprise ArchitectureOn-Premises InfrastructureOperating Systems
Information Technology • Business Intelligence • Consulting
Designs complex, transformational solutions across applications, infrastructure, cloud, and on-premises environments. Collaborates with clients and cross-functional teams to assess requirements, evaluate architectures, create technical plans, develop roadmaps, deliver proof-of-concept implementations, and resolve problems. Ensures solutions meet performance, scalability, cost, and enterprise architecture standards. Mentors colleagues and provides consulting expertise across multi-technology environments.
Top Skills:
Cloud ComputingCobitItilSoaTogafZachman
Big Data • Fintech • Information Technology • Business Intelligence • Financial Services • Cybersecurity • Big Data Analytics
Lead independent manual and automated quality assurance testing for software projects. Develop and contribute to Java-based automation frameworks using BDD, Cucumber, Selenium, and related tools. Execute diverse tests, analyze failures, identify root causes, manage defects through closure, and ensure accurate test documentation. Collaborate with developers on feature-branch certification, apply AI tools, and support agile delivery while maintaining quality, timelines, and customer-focused technology solutions.
Top Skills:
Ai ToolsAmazon EksBddCucumberDevOpsDockerGoogle Cloud Platform (Gcp)JavaJmeterKubernetesSeleniumTest Management Systems
What you need to know about the Chennai Tech Scene
To locals, it's no secret that South India is leading the charge in big data infrastructure. While the environmental impact of data centers has long been a concern, emerging hubs like Chennai are favored by companies seeking ready access to renewable energy resources, which provide more sustainable and cost-effective solutions. As a result, Chennai, along with neighboring Bengaluru and Hyderabad, is poised for significant growth, with a projected 65 percent increase in data center capacity over the next decade.
