Sr Data Architect

Job Description:

At Bank of America we are guided by a common purpose to help make financial lives better through the power of every connection. We do this by driving Responsible Growth and delivering for our clients teammates communities and shareholders every day.

Being a Great Place to Work is core to how we drive Responsible Growth. This includes our commitment to being an inclusive workplace attracting and developing exceptional talent supporting our teammates physical emotional and financial wellness recognizing and rewarding performance and how we make an impact in the communities we serve.

Bank of America is committed to an in-office culture with specific requirements for office-based attendance and which allows for an appropriate level of flexibility for our teammates and businesses based on role-specific considerations.

At Bank of America you can build a successful career with opportunities to learn grow and make an impact. Join us!

Job Description:
This job is responsible for the execution of data architectural solutions for complex initiatives that span multiple Lines of Business and control functions. Key responsibilities include facilitating solution driven discussions working with stakeholders to support adherence to the enterprise data management policy and standards and supporting architecture design reviews to ensure integration of data architecture principles in technology solutions. Job expectations include educating data management teams on enterprise data architectural principles and data management processes and routines.

We are seeking an experienced Sr. Data Architect with deep expertise in AI Controls Responsible AI & enterprise data governance to architect secure compliant and trustworthy AI ecosystems. This senior role is responsible for designing technical guardrails assessing AI control capabilities across platforms and tools and ensuring the safe adoption of AI technologies enterprisewide.

The ideal candidate combines advanced data/AI architecture experience with an expert understanding of AI risks model governance & the technical control frameworks required in regulated environments.

Responsibilities:

• Partners with various technology teams to establish data solutions and architecture for large complex initiatives that align with the enterprise data architecture strategy and strategic technology and platform decisions
• Develops clear and concise responses to questions from senior management and control partners regarding the enterprise data architecture strategy
• Manages multiple priorities in a matrixed environment with attention to detail and accuracy
• Communicates effectively to influence agreement between partners and escalates items as needed to ensure execution activities remain on track
• Ensures all relevant risk financial and compliance policies and standards are met
• Manages relationships with business and technology partners and creates an inclusive and healthy working environment to resolve organizational impediments and blockers
• Educates data management teams on enterprise data architectural principles processes and routines

AI Controls Architecture & Governance

• Design & maintain the architectural framework for AI/ML controls ensuring alignment with enterprise risk & compliance requirements.
• Establish standardized control patterns for data protection access management content filtering prompt governance and safeguard monitoring.
• Evaluate & implement tools for explainability interpretability redteaming bias detection drift monitoring and auditability.
• Partner with Risk Compliance Model Risk Management and InfoSec to harmonize AI architectural controls with enterprise governance frameworks.

Assessment of AI Control Capabilities

• Conduct formal assessments of AI platforms tools and frameworks to determine their control maturity gaps and alignment with enterprise standards.
• Evaluate vendor AI capabilities (e.g. model APIs LLM platforms vector databases AI orchestration tools) against security privacy and operational control requirements.
• Lead control readiness evaluations for new AI solutions including RAG pipelines agents LLM components and MLOps/LLMOps platforms.
• Develop structured assessment criteria for AI guardrails such as:
• Data governance controls
• Model monitoring & explainability tooling
• Hallucination mitigation
• Prompt/response filtering
• Access and identity management
• Logging auditability & model lineage
• Provide recommendations risk mitigation strategies and architectural guidance based on assessment outcomes.

Responsible AI Model Controls & Lifecycle Governance

• Embed Responsible AI principles (explainability fairness transparency robustness) into all AI architectural designs.
• Architect the full model lifecycle with built-in controls including documentation validation approvals testing monitoring and retirement.
• Develop controlled environments for training and deploying models including versioning lineage reproducibility isolation and audit trails.
• Implement continuous monitoring frameworks for compliance drift bias hallucinations and performance degradation.

Leadership & Influence

• Serve as the enterprise expert for AI controls helping shape policy standards and long-term architecture strategy.
• Influence and guide senior leaders engineers and data scientists toward controlled compliant AI adoption.

Required Qualification:

• 10 years in data architecture ML/AI engineering or enterprise architecture roles.
• Demonstrated experience assessing AI control capabilities including evaluating vendors platforms and internal systems.
• Deep expertise in AI/ML governance risk management and Responsible AI frameworks.
• Strong knowledge of enterprise data architecture governance lineage metadata and privacy controls.
• Handson experience with modern data platforms (Databricks Snowflake Azure Data Lake Synapse etc.).
• Proficiency with AI infrastructure (vector databases LLM orchestration platforms embeddings pipelines).
• Strong programming and data engineering skills (Python SQL Spark).
• Experience architecting secure cloud-native solutions (Azure preferred).

Desired Qualifications:

• Experience in regulated industries (financial services healthcare insurance).
• Prior involvement with model risk governance or AI ethics programs.
• Certifications in cloud architecture data engineering or AI governance.
• Experience designing RAG architectures LLMOps workflows and GenAI guardrail frameworks.

Core Competencies

• AI controls design and assessment
• Enterprise data and AI architecture
• Risk-based decision making and technology governance
• Clear communication with executives auditors and technical teams
• Leadership and ability to influence cross-functional groups

Success Measures

• Enterprise-wide adoption of consistent and effective AI controls
• Measurable reduction in AI-related risks
• Strengthened auditability transparency and compliance of AI systems
• Delivery of scalable secure and responsible AI architectures
• Strong partnership with Risk Compliance Legal InfoSec and Engineering teams

Skills:

• Architecture
• Business Analytics
• Critical Thinking
• Data Management
• Data Visualization
• Consulting
• Data Modeling
• Process Design
• Regulatory Compliance
• Risk Management
• Cloud Solutions
• Collaboration
• Data Governance
• Talent Development
• Technical Strategy Development

Shift:

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