[SCFD2MWC] AI Architect

Hello,

Greetings from ZettaMine!!!

FTE Opportunity :- We are hiring an AI and Data Architect for a strategic Enterprise Data, AI, Generative AI & Agentic AI Architecture initiative with a Tier 1 Bank in the Banking and Financial Services (BFSI) domain .

Role: AI and Data Architect

Experience: 10+ Years

Domain: Banking and Financial Services (BFSI)

Role Overview :

We are looking for an experienced AI and Data Architect to design and govern the bank's enterprise data and AI platforms. The role involves building a trusted, well-governed data foundation and enabling AI, Generative AI, and analytics solutions across Deposits, Lending, Cards, Payments, Collections, and Customer Servicing. The architect will work closely with business, risk, and technology teams.

Key Responsibilities

• Define enterprise data architecture, standards, and roadmaps, including data lakehouse, data mesh, and data product patterns.
• Design batch and real-time data pipelines, data models, and integration patterns across core banking systems and digital channels.
• Establish data governance, quality, lineage, and master data management practices that meet regulatory requirements.
• Create AI-ready data foundations for Generative AI, machine learning, and analytics use cases.
• Design AI solutions on enterprise data platforms, including RAG, AI agents, document intelligence, and predictive models.
• Embed responsible AI, model risk management, and data privacy controls into data and AI architecture.
• Guide cloud migration of data platforms and support the retirement of legacy data warehouses.

Delivery Enablement & Oversight

• Provide hands-on architectural guidance to delivery teams throughout the Software Development Life Cycle (SDLC).
• Review data designs, integration approaches, and implementation details to ensure architectural integrity and compliance.
• Support teams in resolving cross-domain integration, performance, and resiliency challenges.
• Work with Risk, Compliance, and Security teams on data privacy, retention, and access controls.

Mandatory Eligibility Criteria

• 10+ years of experience in Data Architecture or Solution Architecture within Banking or Financial Services.
• At least 3 years of experience delivering AI solutions on enterprise data platforms.
• Deep knowledge of banking data domains, including Deposits, Lending, Cards, Payments, Collections, or Customer Servicing.
• Experience building data platforms that support AI, Generative AI, analytics, and regulatory reporting.
• Experience with AI, Generative AI, Agentic AI, RAG, workflow automation, document intelligence, RPA, or process mining.
• Strong understanding of APIs, microservices, cloud platforms, and event-driven architecture.
• Working knowledge of BCBS 239, GDPR, data privacy, and data residency requirements.
• Proven ability to drive business transformation and operational modernization.
• Excellent communication and executive stakeholder management skills.

Required Technology Stack

Data Platforms: Snowflake, Databricks, Azure Synapse, AWS Redshift, Google BigQuery, Delta Lake, Apache Iceberg.

Processing & Streaming: Apache Spark, Apache Kafka, Flink, Debezium (CDC), Airflow, dbt.

Storage & Databases: Amazon S3, ADLS, PostgreSQL, Oracle, NoSQL stores, and graph databases.

Governance & Catalog: Collibra, Alation, Microsoft Purview, Informatica, data lineage, and data quality tools.

Master Data & Modelling: MDM platforms, dimensional modelling, Data Vault modelling, and ER modelling tools.

AI-Ready Data: Feature stores, vector databases, semantic layers, and metadata management for LLM use cases.

AI Platforms & Frameworks: Azure OpenAI, AWS Bedrock, Vertex AI, LangChain, LangGraph, MCP, MLflow, SageMaker, and Azure ML.

AI Safety & Governance: AI guardrails, output evaluation, LLM observability, model risk documentation, and audit logging.

Platform & Integration: Python, SQL, REST APIs, Kubernetes, Terraform, CI/CD pipelines, Power BI, and Tableau.

Key Attributes for Success

• Strategic thinker with a modernization and simplification mindset.
• Strong communicator with the ability to influence stakeholders across business and technology teams.
• Comfortable working in complex, multi-stakeholder, highly regulated environments.
• Trusted advisor who can bridge business objectives and technology execution.
• Strong data-as-a-product mindset, emphasizing clear ownership, quality, and business value.
• Balanced approach to AI adoption, focused on innovation while maintaining strong risk and control measures.
• Passion for leveraging data and AI to optimize processes and improve customer and employee experiences.

How to Apply

Interested candidates can share their updated resume and LinkedIn profile at [email protected] .

Thanks & Regards,

RaviTeja K

ZettaMine