AI Product Engineer

Brown Brothers Harriman•New York, NY

2d•$90,000 - $130,000

About The Position

The Capital Partners (CP) AI Product Engineer translates approved AI concepts, requirements, and business needs into deployed, scalable, secure, maintainable AI-enabled products and solutions. Working with the CP AI Strategy & Transformation Leader and cross-functional partners, the role supports the design, build, configuration, testing, deployment, monitoring, and ongoing improvement of AI-enabled products, agents, copilots, workflows, integrations, and platform capabilities. The engineer helps move priority use cases from pilot concepts to production-ready capabilities with measurable business value and sustainable support models. The role bridges AI strategy, product management, engineering, and operational deployment. It ensures solutions are integrated into existing workflows where appropriate, aligned with approved requirements, tested for readiness, supported by clear technical documentation, and maintainable after release. The engineer also works with business, technology, data, operations, risk, compliance, legal, information security, change management, training, and executive stakeholders to support secure and controlled implementation and continuous improvement.

Requirements

At least 5 years of relevant work experience.
Experience supporting software engineering, product engineering, AI solution delivery, workflow automation, systems integration, platform configuration, or technical product management.
Strong understanding of AI agents, copilots, workflow orchestration, connectors, APIs, authentication patterns, technical testing, monitoring, and production support practices.
Ability to translate business requirements into buildable technical designs, backlog items, agent configurations, workflow specifications, and release artifacts.
Experience working with business, technology, data, operations, risk, compliance, legal, information security, change management, training, and leadership stakeholders.
Strong documentation skills, including solution designs, test plans, release checklists, deployment plans, runbooks, support guides, and technical decision records.

Nice To Haves

Copilot Studio agent build experience.
Experience operating in regulated or complex environments.

Responsibilities

Translate approved AI use cases and business requirements into solution designs, technical architectures, user interactions, system dependencies, agent configurations, integration patterns, and implementation plans.
Build, configure, test, deploy, and maintain AI-enabled products, Copilot Studio agents, workflow automations, connectors, actions, and platform components in alignment with approved requirements.
Partner with Product Owners and Business SMEs to refine functional requirements, define user journeys, clarify acceptance criteria, and support backlog prioritization.
Collaborate with Technology and Data teams to design and implement APIs, connectors, data access patterns, integrations, and platform capabilities.
Configure enterprise data connections, authentication approaches, access controls, and environment settings with appropriate technology and security teams.
Design operational AI workflows, including future-state workflow maps, handoffs, approvals, exception paths, human review, controls, safeguards, and production support needs.
Develop and execute technical test plans covering functional, access, regression, integration, response-quality, and release validation testing.
Document test results, defects, remediation actions, deployment dependencies, operational risks, and readiness considerations.
Provide technical implementation recommendations and tradeoff analysis related to scalability, maintainability, usability, performance, and operational support.
Prepare deployment plans, release checklists, runbooks, implementation evidence, known limitations, support requirements, and technical handoff materials.
Support monitoring and observability, including usage patterns, user experience metrics, performance, reliability, logging, exception tracking, issue triage, and support routines.
Troubleshoot grounding issues, workflow failures, connector issues, access concerns, performance defects, and production support items with AI Context Engineers and Technology teams.
Support platform enhancements and release iterations based on user feedback, monitoring results, and approved backlog priorities.
Collaborate with Information Security, Risk, Compliance, Legal, Technology, and Data partners on secure-by-design implementation, access patterns, data protection, and release practices.
Document technical designs, agent configurations, workflow automations, and integration approaches, ensuring alignment with approved requirements and operating model expectations.
Partner with AI Design & Enablement to provide onboarding, communications, training inputs, and support materials for new AI capabilities.
Partner with AI Context Engineers to align solution configuration with approved knowledge sources, metadata structures, prompt patterns, system instructions, and context maintenance needs.
Capture technical issues, user friction points, reliability trends, and platform constraints to inform continuous improvement.
Reinforce shared engineering standards while enabling practical, localized innovation across CP AI use cases.