Senior Engineer – AI Monitoring & Control Capabilities

Bank of America

Pennington (NJ)

On-site

USD 180,000 - 240,000

Full time

5 hours ago

Be an early applicant

Application generator

Turn this role into an interview — a resume and cover letter built around what this employer wants.

Get past ATS filters

Job summary

Bank of America seeks a senior engineer to own the end-to-end delivery of on-prem vendor AI-related applications within OpenShift. You will build APIs, guardrails, and observability for enterprise AI Agent solutions, ensuring audit-ready, scalable production services.

You will lead cross-functional teams, drive architectural standards, and contribute to budgeting and planning while maintaining a sense of urgency and solid operational judgment.

Qualifications

Bachelor's or Master's degree in CS/DS/MIS or equivalent experience.
13+ years of software engineering designing, building, and scaling production apps.
Strong Python, data/ML libraries; hands-on OpenShift/Kubernetes experience.
Proven production experience with LLM-/RAG-based apps and scaling.
Experience building APIs and integrating third-party platforms.
Experience with AI Agents, OpenAI APIs, LangChain.
Understanding of inference performance optimization and guardrails.

Responsibilities

Own delivery of critical vendor apps in a fully on-prem OpenShift environment, hitting milestones.
Build APIs and integrations linking guardrail and observability to AI Agent solutions.
Establish workflows monitoring performance, latency, throughput, quality, and guardrail efficacy.
Implement model evaluation frameworks using LLM-as-a-Judge and specialized models.
Develop observability dashboards and alerts with Grafana; ensure audit readiness.
Troubleshoot production issues, improve scalability and resilience for critical services.
Contribute to evaluation methodologies and guardrails for AI systems.
Lead engineers, set development standards, and drive cross-functional improvements.
Contribute to budgeting, forecasting, and management of supported apps.

Skills

Automation

Influence

Result Orientation

Stakeholder Management

Technical Strategy Development

Application Development

Architecture

Risk Management

Solution Design

Agile Practices

Analytical Thinking

Collaboration

Data Management

Solution Delivery Process

Education

Bachelor's or Master's degree in Computer Science, Data Science, MIS, a related field, or equivalent practical experience

Tools

OpenShift

Kubernetes

OpenAI APIs

LangChain

Grafana

Splunk

LangSmith

Job description

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 is a critical-delivery role responsible for engineering and operating vendor applications end to end within an on-premises OpenShift platform, directly supporting the enterprise's AI monitoring, controls, and governance commitments. You will develop and integrate application components, deploy and scale containerized services, and provide the production support that keeps these services reliable, performant, and audit-ready.

The domain is AI Agent operations. The applications you support deliver guardrails and observability for LLM powered systems across the enterprise, enabling the model observability, traceability, and evaluation needed to meet risk management, compliance, and regulatory expectations. Because this capability underpins key delivery milestones, the role demands strong engineering discipline, sound operational judgment, and a sense of urgency.

The ideal engineer learns new tools and environments quickly, brings a pragmatic build-and-operate mindset, and can lead cross-functional initiatives without formal authority.

Responsibilities

Own delivery of critical vendor applications from build through production support in a fully on-premises OpenShift environment, meeting committed milestones and quality expectations.
Build and maintain APIs and integrations connecting vendor guardrail and observability platforms to enterprise AI Agent solutions.
Establish and manage workflows that monitor performance, safety, latency, throughput, quality, and guardrail effectiveness in support of AI risk and control objectives.
Implement and maintain model evaluation frameworks using LLM-as-a-Judge and specialized language models.
Develop observability dashboards and alerting using Grafana or similar tools, producing audit-friendly evidence and traceability.
Troubleshoot production issues and improve scalability, resilience, and operational efficiency to sustain availability for critical business services.
Contribute to evaluation methodologies and guardrail controls for agentic and multi-step AI systems.
Lead and mentor engineers, establish development standards, and drive process improvements across cross-functional delivery.
Provide input into financial planning, budget tracking, forecasting, and management of supported applications and services.

Required Qualifications

Bachelor's or Master's degree in Computer Science, Data Science, MIS, a related field, or equivalent practical experience.
13+ years of software engineering experience designing, building, and scaling production applications.
Strong proficiency in Python, including common data and ML libraries. Hands-on experience deploying and operating containerized workloads on OpenShift or Kubernetes.
Proven experience taking LLM- or RAG-based applications into production and maintaining them at scale.
Experience building APIs and integrating third-party platforms.
Working experience with AI Agents development, including OpenAI APIs and LangChain.
Practical understanding of inference performance optimization. Experience applying guardrails, observability, and model-based evaluation to AI applications.
Experience delivering within Agile and Agile-at-scale environments against firm timelines.
Proven ability to influence outcomes and meet delivery commitments in a matrixed organization without direct authority. Strong problem-solving, communication, and stakeholder management skills.

Desired Qualifications

Experience delivering technology solutions within a large, complex, highly regulated enterprise, preferably financial services.
Fast learner able to ramp quickly on new technologies and tools.
Experience with annotation pipelines, feedback loops, fine-tuning, and model alignment techniques.
Familiarity with prompt versioning and lifecycle management.
Experience with vendor-provided guardrail and observability platforms such as Galileo, LangSmith, and Splunk.
Working knowledge of additional AI Agents frameworks such as LlamaIndex or Haystack.
Familiarity with evaluation and guardrails for agentic, multi-step AI workflows.
Collaborative and self-directed work style supporting engineering teams.

Skills