Senior Engineer- Agentic AI

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 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.

Position Summary:

Were seeking a Senior Engineer to lead the design and implementation of Agentic AI across the SDLC. You will define the strategy architecture and operating model for applying GitHub Copilot Microsoft Copilot Studio Azure AI Foundry and the Microsoft Agentic Frameworkenhanced by RAG context engineering prompt engineering and knowledge graphsto automate and elevate developer workflows from planning through production. You will partner with product platform risk and delivery teams to drive measurable outcomes ensure responsible use and scale adoption across the enterprise.

Responsibilities:

Strategy & Roadmap:

- Define the enterprise AgenticAIinSDLC strategy operating model and multiyear roadmap aligning with business objectives enterprise architecture and developerproductivity goals.

- Prioritize epics and features in the backlog and drive crossportfolio execution to accelerate value realization and adoption.

Architecture & Design:

- Architect agentic workflows using the Microsoft Agentic Framework and integrate them with SDLC systems including issue trackers repositories CI/CD pipelines quality and security gates and observability platforms.

- Design context architecturegrounding data state management retrieval patterns prompt templates and cachingto ensure reliable highquality outcomes. - Design RAG solutions using enterprise content vector search and knowledge graphs and define reference architectures and guardrails for Copilotbased coding testing and automation.

Engineering & Delivery:

- Lead delivery of AI agents that automate SDLC tasks such as requirements analysis design reviews test generation traceability codequality enforcement documentation updates and release readiness.

- Build Copilots with Copilot Studio integrating plugins enterprise search and workflow actions and operationalize models in Azure AI Foundry with full lifecycle support for evaluation monitoring safety and CI/CD/CT pipelines for prompts and agents.

Data RAG and Knowledge Graphs:

- Define ontology and schema for domain knowledge graphs and integrate code metadata service catalogs architectural decisions and control libraries to create robust retrieval ecosystems.

- Implement strong data governance for retrieval sources ensuring correct handling of sensitive data adherence to residency and retention rules and delivery of highquality grounding pipelines.

LLMOps / MLOps:

- Establish LLMOps practices including prompt/version management evaluation suites for quality safety bias and hallucination and offline/online experiments such as A/B tests.

- Maintain golden datasets and benchmarks aligned to SDLC goals like codequality improvement vulnerability reduction and MTTR reduction.

Security Compliance & Risk:

- Partner with Risk Legal Privacy InfoSec and Model Risk to define responsibleAI patterns including policyascode controls auditable logs databoundary enforcement content safety and humanintheloop review.

- Navigate governance and control processes to ensure solutions meet regulatory and modelrisk expectations.

Change Management & Adoption:

- Lead developer onboarding enablement and communities of practice by sharing prompt patterns reusable tools and exemplars.

- Track and communicate value through KPIs and OKRs and provide progress updates and insights to executive stakeholders

Required Qualifications:

• 10 years in software engineering/architecture with 2 years leading AI/LLM or intelligent automation solutions in production ideally at enterprise scale.

• Proven experience implementing Agentic AI solutions (tooluse orchestration planning memory/state) and integrating them with SDLC platforms.

• Handson with GitHub Copilot (orglevel policies telemetry governance) Microsoft Copilot Studio (plugins/connectors) and Azure AI Foundry (Prompt Flow eval/monitoring safety and compliance).

• Deep knowledge of RAG prompt & context engineering and vector search; experience building knowledge graphs and integrating them into retrieval workflows.

• Strong grasp of LLMOps/MLOps: dataset curation eval design regression testing for prompts/agents observability safety/guardrails rollout strategies.

• Expertise with SDLC toolchains: GitHub CI/CD IaC testing frameworks SAST/DAST artifact repositories service catalogs and runbooks.

• Ability to lead crossfunctional programs manage risk and communicate with executive and engineering stakeholders.

• Familiarity with responsible AI principles data privacy and secure software development practices.

Desired Qualifications:

• Experience in regulated industries and with Model Risk Management or similar governance.

• Knowledge of enterprise search graph databases and metadata management.

• Background with cloud platforms (Azure preferred) container orchestration (Kubernetes) and policyascode.

• Exposure to evaluation techniques (task success safety toxicity grounding fidelity hallucination rates) and A/B testing for agents.

Shift:

Hours Per Week:

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