Principal Engineer - RAG Database & Embeddings Architect
Principal Engineer - RAG Database & Embeddings Architect
Charlotte, North Carolina
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**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 and providing a culture of caring is core to how we drive Responsible Growth. We are intentional about fostering an inclusive workplace where every teammate has the opportunity to succeed, build a career and contribute to our shared success. This includes attracting and developing exceptional talent, recognizing and rewarding performance, and supporting our teammates’ physical, emotional, and financial wellness through affordable, competitive and flexible benefits.
We value the unique perspectives individuals bring from all backgrounds and career paths - whether shaped by military service, community college education, or a wide range of work and life experiences. These journeys foster resilience, leadership and innovation, strengthening our workforce and positively impact the communities we serve.
Bank of America is committed to an in-office culture that supports collaboration, engagement, and career development. Our approach includes clear in-office expectations, while providing an appropriate level of flexibility based on role-specific responsibilities and business needs.
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 defining and leading the engineering approach for solutions at the program or portfolio level, to deliver significant business outcomes. Key responsibilities include continuously improving the design, quality, and reuse of the solution and delivering technology enablers that improve development efficiencies for the solution. Job expectations include familiarity with at least one area of engineering, acting as a “go to” reference across the organization, and applying knowledge to improve technical competencies through recruitment and development activities.
Developer Experience (DevEx) provides enterprise technical standards and common technical services, platforms, and tools that are leveraged by delivery teams across all lines of business. Within the **SDLC Software Delivery Lifecycle** program, this role leads portfolio product delivery strategy and execution for enterprise software delivery capabilities, ensuring the right investments, operating model, governance, and prioritization are in place to improve how internal technical users build, test, and deliver software at scale.
The RAG Database & Embeddings Architect is responsible for designing, building, and governing the vector database and retrieval architecture that powers enterprise Retrieval-Augmented Generation systems. This role focuses on embeddings, vectorization strategies, semantic search, indexing, metadata modeling, hybrid retrieval, relevance tuning, and performance optimization.
This engineer will define how enterprise knowledge is represented, stored, retrieved, ranked, and refreshed for use by LLM-powered applications.
**Responsibilities:**
+ Develops the engineering approach for the entire program/portfolio solution and works with Architecture, to develop/analyze/deliver the implementation of technical enablers
+ Leads the planning, definition, and design of the complex features which span multiple teams and explore solution alternatives
+ Creates ideas on designing complex technology and solution development approaches
+ Leads the technical oversight for teams in solution development including design reviews and code within own domain
+ Defines the technology tool stack for the solution within ranged of internally approved and supported technologies
+ Explores state-of-the-art technologies to improve development efficiencies, quality of test/QA coverage, and release management
+ Leads and is responsible for the end-to-end test strategy/creation/adherence, and the integration between teams for a program/portfolio solution
+ Improve the experience for our developers, making it easier to deliver industry-leading solutions, while managing work efficiently and with the right controls
+ Advance our technology platforms through innovation
+ Reduce risk and improve quality across our technology portfolio by aligning to a single enterprise architecture strategy and delivering governance that enables consistency, integration and automation
+ Design and own the architecture for enterprise RAG data stores, including vector databases, document stores, metadata stores, and hybrid search layers.
+ Define embedding strategies across structured, semi-structured, and unstructured content.
+ Evaluate and select embedding models based on accuracy, latency, cost, domain fit, multilingual needs, and operational constraints.
+ Design vectorization workflows including chunking, embedding generation, indexing, versioning, and re-embedding lifecycle management.
+ Implement semantic, keyword, metadata-filtered, and hybrid retrieval patterns.
+ Optimize retrieval quality using similarity metrics, reranking, query expansion, metadata boosting, and relevance feedback.
+ Establish standards for vector schema design, namespace strategy, document lineage, source attribution, and access-control-aware retrieval.
+ Partner with data pipeline engineers to ensure ingestion processes produce high-quality, retrievable content.
+ Partner with context engineers to tune retrieval outputs for downstream LLM consumption.
+ Define observability for retrieval quality, including recall, precision, latency, cost, freshness, and hallucination risk indicators.
+ Lead technical evaluation of vector database platforms and retrieval frameworks.
+ Provide engineering leadership, design reviews, mentoring, and architectural guidance across AI platform teams.
+ Serve as a senior technical authority for enterprise AI platform engineering.
+ Own architecture decisions that impact multiple teams, systems, or domains.
+ Create reusable patterns, reference architectures, standards, and engineering guardrails.
+ Mentor senior engineers and influence technical direction without requiring direct reporting authority.
+ Balance innovation with operational reliability, security, compliance, scalability, and cost management.
+ Communicate complex AI and data engineering concepts clearly to engineering, product, risk, security, and executive stakeholders.
**Required Qualification:**
+ 10+ years of software engineering, data engineering, platform engineering, or AI engineering experience.
+ 5+ years designing large-scale enterprise systems.
+ 2+ years working with LLM, RAG, vector search, semantic search, or AI platform capabilities.
+ Experience operating systems in regulated, security-conscious, or enterprise-scale environments.
+ Extensive experience designing production-grade search, indexing, or database systems.
+ Strong understanding of vector databases, embeddings, similarity search, approximate nearest neighbor algorithms, and retrieval optimization.
+ Experience with RAG architectures and enterprise-scale knowledge retrieval.
+ Hands-on experience with platforms such as Azure AI Search, Cosmos DB vector search, Pinecone, Weaviate, Milvus, OpenSearch, Elasticsearch, PostgreSQL/pgvector, or equivalent.
+ Experience with embedding models from providers such as OpenAI, Azure OpenAI, Cohere, Hugging Face, or open-source model ecosystems.
+ Strong background in distributed systems, database design, API design, and performance tuning.
+ Experience designing metadata models, access control filtering, document provenance, and auditability.
+ Ability to define engineering patterns and standards used across multiple teams.
+ Proven ability to lead architecture across multiple engineering teams.
+ Strong written and verbal communication skills.
+ Bachelor’s degree in Computer Science, Engineering, Information Systems, Applied Mathematics, or a related technical field
**Desired Qualifications:**
+ Experience with hybrid retrieval, reranking models, knowledge graphs, or entity-aware retrieval.
+ Experience supporting regulated or enterprise environments with security, compliance, lineage, and privacy requirements.
+ Experience with LLM evaluation, retrieval evaluation, and automated relevance testing.
+ Familiarity with model drift, embedding drift, and re-indexing strategies.
+ High-quality retrieval architecture that improves LLM answer accuracy and reduces hallucinations.
+ Scalable vector database strategy supporting multiple enterprise domains.
+ Clear standards for embeddings, metadata, indexing, and retrieval evaluation.
+ Measurable improvements in retrieval precision, recall, latency, and cost efficiency.
+ Enterprise architecture
+ Distributed systems design
+ AI platform engineering
+ Data governance and security
+ Cloud-native engineering
+ Observability and operational excellence
+ Technical strategy and roadmap development
+ Cross-functional influence
+ Vendor and platform evaluation
+ Production support and continuous improvement
**Skills:**
+ Automation
+ Influence
+ Result Orientation
+ Stakeholder Management
+ Technical Strategy Development
+ Application Development
+ Architecture
+ Business Acumen
+ Risk Management
+ Solution Design
+ Agile Practices
+ Analytical Thinking
+ Collaboration
+ Data Management
+ Solution Delivery Process
**Shift:**
1st shift (United States of America)
**Hours Per Week:**
40
Bank of America and its affiliates consider for employment and hire qualified candidates without regard to race, religious creed, religion, color, sex, sexual orientation, genetic information, gender, gender identity, gender expression, age, national origin, ancestry, citizenship, protected veteran or disability status or any factor prohibited by law, and as such affirms in policy and practice to support and promote the concept of equal employment opportunity, in accordance with all applicable federal, state, provincial and municipal laws. The company also prohibits discrimination on other bases such as medical condition, marital status or any other factor that is irrelevant to the performance of our teammates.
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Bank of America aims to create a workplace free from the dangers and resulting consequences of illegal and illicit drug use and alcohol abuse. Our Drug-Free Workplace and Alcohol Policy (“Policy”) establishes requirements to prevent the presence or use of illegal or illicit drugs or unauthorized alcohol on Bank of America premises and to provide a safe work environment.
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. Should you be offered a role with Bank of America, your hiring manager will provide you with information on the in-office expectations associated with your role. These expectations are subject to change at any time and at the sole discretion of the Company. To the extent you have a disability or sincerely held religious belief for which you believe you need a reasonable accommodation from this requirement, you must seek an accommodation through the Bank’s required accommodation request process before your first day of work.
This communication provides information about certain Bank of America benefits. Receipt of this document does not automatically entitle you to benefits offered by Bank of America. Every effort has been made to ensure the accuracy of this communication. However, if there are discrepancies between this communication and the official plan documents, the plan documents will always govern. Bank of America retains the discretion to interpret the terms or language used in any of its communications according to the provisions contained in the plan documents. Bank of America also reserves the right to amend or terminate any benefit plan in its sole discretion at any time for any reason.