AI Architect - MDM & Data Governance

Location: Noida | 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.