Sr. Engineer

Bank of America•Pennington, AL

2d•Onsite

About The Position

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! 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. The AI Lead is responsible for providing LoB-level thought leadership, scalable AI architecture, and end-to-end delivery of artificial intelligence solutions from proof of concept through production. This role drives the adoption of modern AI, LLM, RAG, and agentic design patterns across multiple teams and applications, ensuring solutions are secure, reusable, well-governed, and aligned to business outcomes. The role also develops understanding of Bank’s internal AI frameworks & design standards to enable solution that meet enterprise design & implementation requirements. The AI Lead contributes to defining and evolving the AI and agentic architecture roadmap, translating business needs into production-ready AI capabilities while enforcing consistent design, development, and quality standards. This role plays a critical part in enabling teams to deliver AI features efficiently by leveraging shared frameworks, reusable components, and standardized delivery processes.

Requirements

7+ years in software engineering
2 years in AI and Data platform
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
AI & GenAI: LLM applications, RAG, Text-to-SQL, LangGraph, LangChain, MCP (Model Context Protocol), Prompt Engineering, Vector Similarity Hybrid Search
Models: Microsoft 365 Copilot & Copilot Studio, GPT-4/ChatGPT (OpenAI), Claude Sonnet/Opus (Anthropic), Llama 3 (Meta), Human-in-the-loop Workflows
ML & Deep Learning: Transformer Architecture, Self-Attention, Tokenization, Embeddings, Chunking Strategies, Fine-Tuning Concepts (SFT, LoRA, QLoRA), RLHF, Neural Networks, Hallucination Detection
Data Engineering: Handling structured & unstructured data, real-time data ingestion, Databricks, Apache Spark, Cloudera, S3, Data Pipeline Optimization
Languages & Frameworks: Python, Java, FastAPI, REST APIs, SQL, Node.js
Cloud & Infrastructure: MS Azure, S3, ElastiCache, Containerization, Jenkins, CI/CD, OpenShift, Artifactory

Responsibilities

Ensures that the design and engineering approach for complex features are consistent with the larger portfolio solution
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
Opportunity & Inclusion Champion: Models an inclusive environment for employees and clients, aligned to company Great Place to Work goals.
Manager of Process & Data: Demonstrates deep process knowledge, operational excellence and innovation through a focus on simplicity, data based decision making and continuous improvement.
Enterprise Advocate & Communicator: Communicates enterprise decisions, purpose, and results, and connects to team strategy, priorities and contributions.
Risk Manager: Ensures proper risk discipline, controls and culture are in place to identify, escalate and debate issues.
People Manager & Coach: Provides inspection, coaching and feedback to motivate, differentiate and improve performance.
Financial Steward: Actively manages expenses and budgets in alignment with objectives, making sound financial decisions.
Enterprise Talent Leader: Assesses talent and builds bench strength for roles across the organization.
Driver of Business Outcomes: Delivers results by effectively prioritizing, inspecting and appropriately delegating team work.
Providing LoB-level thought leadership, scalable AI architecture, and end-to-end delivery of artificial intelligence solutions from proof of concept through production.
Drives the adoption of modern AI, LLM, RAG, and agentic design patterns across multiple teams and applications, ensuring solutions are secure, reusable, well-governed, and aligned to business outcomes.
Develops understanding of Bank’s internal AI frameworks & design standards to enable solution that meet enterprise design & implementation requirements.
Contributes to defining and evolving the AI and agentic architecture roadmap, translating business needs into production-ready AI capabilities while enforcing consistent design, development, and quality standards.
Plays a critical part in enabling teams to deliver AI features efficiently by leveraging shared frameworks, reusable components, and standardized delivery processes.