Associate Director

AI Architect – MDM & Data Governance

Location: [Noida/ Pan India] | Practice: MDM & Data Governance CoE | Experience: 8+ years]

About the Role

We are looking for an AI Architect to lead the design and evolution of AI-driven solutions within our Master Data Management (MDM) and Data Governance practice. This role sits at the intersection of data architecture and applied AI — designing intelligent accelerators (matching, stewardship automation, DCR resolution, data quality agents) that augment platforms like Reltio, Informatica IDMC, and Veeva Network, while also playing a key role in pre-sales and solution architecture for client pursuits.

Key Responsibilities

AI Solution Architecture

Architect AI/ML and agentic solutions for core MDM and data governance use cases: match & merge, survivorship, DCR automation, anomaly detection, data quality scoring, and stewardship workflows

Design and own the technical architecture for AI accelerators (e.g., Smart DCR Agents, Potential Match Resolution Agents, Agentic HCP/HCO Mastering engines), ensuring scalability, explainability, and platform-agnostic integration

Evaluate and select appropriate AI/ML techniques (LLMs, classical ML, rules + ML hybrid models) based on use case, data volume, and latency requirements

Define reference architectures integrating AI layers with MDM platforms (Reltio, Informatica IDMC, Veeva Network) and governance/catalog tools (Collibra, Atlan, Alation)

Optimization & Continuous Improvement

Drive performance tuning, accuracy benchmarking, and continuous optimization of existing AI accelerators and agents

Establish feedback loops (human-in-the-loop stewardship, model retraining cadences) to improve match precision and reduce false positives/negatives over time

Monitor and report on AI accelerator ROI metrics (cycle time reduction, automation rate, data quality lift) to clients and internal leadership

Identify opportunities to modernize legacy rule-based MDM/DG processes with AI-native alternatives

Pre-Sales & Client Engagement

Lead AI/technical solutioning for RFP/RFI responses, including architecture diagrams, effort estimation, and differentiation narrative

Partner with CoE and sales leadership to build and refine GTM assets (battlecards, demo environments, POV decks) for AI-powered MDM and governance offerings

Present AI architecture and accelerator capabilities directly to client technical and business stakeholders, including live demos and technical deep-dives

Support discovery workshops to assess client data maturity and identify high-value AI use cases within MDM/DG scope

Delivery & Cross-Functional Leadership

Provide architectural oversight during implementation, ensuring delivery teams correctly integrate AI components with MDM/DG platforms

Collaborate with data engineering, MDM, and governance teams to ensure AI solutions align with data governance policies, security, and compliance requirements

Mentor data scientists, engineers, and consultants on AI architecture best practices within the CoE

Maintain reusable architecture patterns, technical documentation, and accelerator roadmaps for the CoE

Required Qualifications

8+ years of experience in AI/ML architecture, data architecture, or related technical consulting roles

Demonstrated experience designing and deploying AI/ML or agentic solutions in production environments

Strong working knowledge of MDM concepts (match/merge, survivorship, golden records) and data governance principles (stewardship, DCR workflows, policy management)

Hands-on experience with at least one MDM platform (Reltio, Informatica IDMC, Veeva Network) and one governance/catalog tool (Collibra, Atlan, Alation)

Proficiency in ML/LLM frameworks and cloud AI services (e.g., Python, Databricks, Snowflake, Azure/AWS AI services, LLM APIs)

Experience contributing to RFP/RFI responses and client-facing technical presentations

Strong communication skills with the ability to translate complex AI architecture into business value for non-technical stakeholders

Preferred Qualifications

• Experience in life sciences/pharma data environments (HCP/HCO mastering, commercial data ecosystems)

• Prior experience building agentic AI systems or AI copilots for enterprise data workflows

• Familiarity with prompt engineering, RAG architectures, and agent orchestration frameworks

• Relevant certifications in cloud AI/ML platforms or enterprise architecture