AI SME

Job Title : AI SME

Location: Bangalore

PURPOSE OF THE ROLE

The AI SME is responsible for designing, industrializing, and scaling AI/ML solutions that deliver measurable business value. This role bridges business, data, and technology, ensuring AI capabilities are embedded into operational workflows and drive outcomes across markets and products.

WHAT WILL YOUR MAIN RESPONSIBILITIES BE

Identify and prioritise high-value AI use cases aligned to business priorities.

Translate complex business problems into scalable AI solutions with clear value outcomes.

Own end-to-end delivery of AI initiatives spanning from initial idea, pilot, production, through to final adoption.

Design and guide development of AI/ML models and intelligent systems.

Drive deployment, integration, and lifecycle management (MLOps) of AI/ML capabilities into data engineering and operational processes.

Ensure AI solutions are secure, scalable, and aligned to enterprise platforms.

Define and enforce strict standards for data quality, model validation, and continuous monitoring.

Embed Responsible AI principles (including fairness, explainability, and compliance across solutions.

Ensure strict adherence to data governance, privacy, and security requirements across all platforms.

Apply deep domain expertise to ensure AI outputs are accurate, relevant, and actionable for the business.

Translate complex model outputs into clear business insights and strategic decision support.

Partner closely with product and business teams to seamlessly embed AI into daily operations.

Drive the transition from proof-of-concept to scaled production solutions across markets and teams.

Ensure wide adoption across markets, tracking post-deployment impact, user adoption and performance.

Continuously optimise AI solutions for performance, cost-efficiency, latency, and scalability.

Provide technical leadership, guidance, and mentoring to AI engineers and data scientists.

Contribute to building overall AI capability, methodologies, and technical standards across the organisation.

Collaborate proactively across global teams to ensure aligned, modular, and reusable AI assets.

Work proactively and independently to address project requirements and articulate issues/challenges to reduce project delivery risks.

EXPERIENCES & QUALIFICATIONS

The ideal candidate will be an experienced AI, data, and analytics specialist with hands-on expertise in delivering AI use cases, machine learning models, and analytics solutions within complex business environments. They will have practical experience across the solution lifecycle, including requirements gathering, design, delivery support, and continuous improvement.

They will have a strong understanding of data management, BI, analytics engineering, and emerging technologies, along with good commercial judgment and the ability to work collaboratively with cross-functional teams. The successful candidate will be proactive, delivery-focused, and comfortable taking a hands-on approach to problem solving and implementation.

Necessary Experience & Qualifications

Essential

Overall 8-10+ years of experience in technical delivery of data-related product requirements, data science, and advanced analytics products/solutions.

Strong experience in AI/ML, data science, or advanced analytics with a proven track record of delivering AI solutions in scaled production environments.

Deep understanding and experience with Agile/DevOps/ML development lifecycles from conception to delivery in the Data & Analytics area with focus is in LLMs, RAG architectures, and AI agents

Hands-on experience with Python and core ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).

Solid understanding of data engineering, data pipelines, and handling large-scale datasets.

Strong ability to translate business problems into technical AI solutions and articulate technical specifications.

Experience in working with and leading multi-skilled, cross-functional global teams to drive product requirements.

Excellent stakeholder management and communication skills with senior business stakeholders / Business leads.

Preferred

Experience with cloud platforms such as Azure, AWS, or Google Cloud Platform (Azure Preferred).

Exposure to MLOps, CI/CD Deployment Process, and model deployment frameworks.

Knowledge of AI governance, ethics, Responsible AI, and regulatory compliance.

Education:

Ideal candidates would preferably have a master’s or bachelor’s degree in computer science data science, Engineering, Mathematics, or a related field. Relevant certifications in AI Machine Learning, or Cloud platforms are desirable.

SKILLS – [Skills List]

AI & Machine Learning Expertise: Deep understanding of traditional ML, Deep Learning, and Generative AI (LLMs, RAG architectures, and AI agents).

Azure Cloud & Analytics Platforms: Hands-on familiarity with enterprise cloud ecosystems, specifically Azure OpenAI, Azure Databricks, and Microsoft Fabric.

Data Products & BI Solutions: Proven track record in designing robust data products and advanced Power BI reporting/dashboard development.

AI & Analytics Use Case Development: Ability to identify, scope, and prioritize high-value AI and data science opportunities.

Techno-Functional Requirement Analysis: Acting as the bridge between complex technical engineering and functional business needs.

AI Lifecycle Management (MLOps): Familiarity with operationalizing AI, including model deployment, monitoring, and lifecycle management in production.

Responsible AI & Governance: Solid understanding of AI ethics, risk mitigation, and data privacy compliance in enterprise deployments.

Complex Transformation Support: Experience guiding and scaling technical solutions within large-scale, global digital transformation programs.

Delivery & Value Awareness: Strong grasp of project lifecycles, cross-team dependencies, timeline management, and tracking ROI.

Global Stakeholder Collaboration: Exceptional communication skills with a proven ability to manage senior stakeholder expectations across matrixed teams.

Analytical Problem Solving: Strong decision support capabilities with the agility to adapt quickly to fast-evolving tools and methods.

Our commitment to Equality, Diversity & Inclusion

Unilever embraces diversity and encourages applicants from all walks of life! This means giving full and fair consideration to all applicants and continuing development of all employees regardless of age, disability, gender reassignment, race, religion or belief, sex, sexual orientation, marriage and civil partnership, and pregnancy and maternity.

Note: "All official offers from Unilever are issued only via our Applicant Tracking System (ATS). Offers from individuals or unofficial sources may be fraudulent - please verify before proceeding."

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