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!
Key Skills for This Role
azureelasticsearchhuggingfaceopenaipostgresql
Full Job Posting
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
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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.
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:
Hours Per Week:
About Bank of America
Financial Services10,001+Founded 1904
Bank of America is a multinational financial services company and one of the largest banks in the United States. It provides banking, investing, asset management, and other financial products and services to individuals, businesses, and institutions worldwide.
