Senior Data Engineer-AI/BI Analytics

Bank of America Corporation•Newark, DE

41d•Onsite

About The Position

Join a groundbreaking team at Bank of America, at the forefront of innovation in AI. We are building the next generation of Gen AI platform, empowering new AI initiatives across Consumer, Small Business, Global Banking, and Wealth organizations. This is a unique opportunity to contribute to a critical platform that will enable secure, scalable, and high-performance AI capabilities across the organization. We value curiosity, collaboration, and a passion for pushing the boundaries of what's possible with AI. This position is focused on design, build, and serve the Gen AI inferencing capabilities. This job is responsible for defining and leading the engineering approach for complex features to deliver significant business outcomes. Key responsibilities of the job include delivering complex features and technology, enabling development efficiencies, providing technical thought leadership based on conducting multiple software implementations, and applying both depth and breadth in a number of technical competencies. Additionally, this job is accountable for end-to-end solution design and delivery.

Requirements

10+ years strong experience designing and delivering AI, ML, Data platform, and advanced analytics platforms capabilities using open-source technologies in large enterprise environment
Experience with emerging technologies e.g. of GenAI (public and open source), MCP, Agents, AI BI etc.
Hands-on experience on data science, big data, cloud, governance technologies
Experience architecting next generation AI analytical product delivery to all levels of users in organization using self-service interfaces
Proven track record in data, analytics, insight and AI/ML platforms supporting multiple business units.
Experience in designing, developing, and maintaining software frameworks using Open-Source technologies such as Python, Spark, Jupyter, FastAPI, LabelStud.io, Ragas etc.
Strong working experience of how metadata management, semantic layers, labeling, annotations is important for enabling AI BI, MCP, Agents, Data Assistants etc.
Experience with using various Open source and Cloud model for AI BI, Summarization etc., and tuning those models and deployment to provide higher throughput for latency and cost optimizations.
Experience of building RAG with knowledge base, data sources and Vector Store platforms such as Redis, Solar, Postgres DB, FAISS, Teradata, Oracle, SQL Server, Hadoop etc.
Hands on experienced building RAG, RAG Fusion, CAG etc.
Experience with various inference metrics, and related monitoring and observability.
Experience with serving multiple tenants/clients with model endpoints with secure boundaries.
Experience with AI gateway, OPA, authentication & authorization, policy as code, API based systems Integration, cost management, and model routing

Nice To Haves

Experience developing Gen AI training and RAG platform with open-source model, inferencing & servicing capabilities, MCP modules etc.
Hands on experience on driving and maintaining a culture of quality, innovation, and experimentation.
Research on new tools and capabilities for better UI and UX for advanced analytics platform, quick prototype and demonstrate the features and capabilities, and participate on various user forums.

Responsibilities

Assembles large, complex data sets that meet functional and non-functional requirements, ensuring that the design and engineering approach is consistent across multiple systems
Maintains, improves, cleans, and manipulates large data for operational and analytics data systems, builds complex processes supporting data transformation, data structures, metadata, data quality controls, dependency, and workload management, and communicates required information for deployment, maintenance, and support of business functionality
Utilizes multiple architectural components in the design and development of client requirements and collaborates with development teams to understand data requirements and ensure the data architecture is feasible to implement
Defines and builds data pipelines to enable data-informed decision making, ensuring adherence to release processes and risk management routines
Contributes to existing test suites including integration, regression, and performance, analyzes test reports, identifies any test issues and errors, and leads triage of underlying causes
Leads the identification of gaps in data management standards adherence and works with appropriate partners to develop plans to close gaps, leading concept testing and conducting research to prototype toolsets and improve existing processes
Mentors Data Engineers in the delivery and release of continuous integration and continuous delivery events and defines key performance indicators and internal controls
Ensures that the design and engineering approach for complex features are consistent with the larger portfolio solution. Accountable for the availability, stability, scalability, security, and recoverability enabled by the designs.
Define the technology tool stack for the solution and evaluate and adapt new testing tool/framework/practices for team(s)
Enables team(s)/applications with Continuous Integration/Continuous Development (CI/CD) capabilities and engages with other technical stakeholders pertaining to efficient functioning of CI-CD pipeline
Guides and influences team(s) on design and best practices for high code performance -e.g. pairing, code reviews
Provides end-to-end delivery of complex features, including automation, for either a single team or multiple teams, at the program level
Conducts research, design prototyping and other exploration activities such as evaluating new toolsets and components for release management, CI/CD, and features
Works with stakeholders to establish high-level solution needs and with architects for technical requirements
Proficient written and verbal communication skills to support and shape the platform and clearly articulate technical designs and concepts; and to communicate effectively with all levels within the organization
Design and execute the implementation plans to both move forward strategically, while at the same time ensuring the current technology stack is supporting current needs.
Manage multiple priorities, and simultaneously engage with multiple teams worldwide.
Coach and mentor team members