Agentic AI Engineering Manager

Job Overview

Pay Range: $105hr - $110hr

The role involves leading agentic AI-driven QA transformation by designing autonomous test automation systems, integrating AI-assisted and agentic testing models into enterprise CI/CD pipelines, and driving governance, strategy, and continuous improvement across QA engineering functions.

Requirement/Must Have:

• Bachelor’s degree in a relevant field such as Computer Science, Engineering, or Business.
• 5 to 10 years of experience in managing testing efforts within a large-scale Agile environment, particularly in financial services.
• Strong understanding of Agile methodologies and testing techniques.
• Proven experience in developing and executing automated test cases for web and mobile applications used in marketing.
• Strong understanding of marketing and martech platforms.
• Comprehensive understanding of risk and controls, audit requirements, and ability to work with diverse stakeholders across the organization.

Experience:

• Experience managing QA/testing efforts in enterprise Agile environments.
• Experience working in financial services domain preferred.

Responsibilities:

• Design and implement agent-based QA systems that autonomously generate, execute, and maintain automated test scripts using intake forms, user stories, and acceptance criteria.
• Lead transition from traditional test automation to AI-assisted and agentic testing models including self-healing tests, adaptive coverage, and intelligent test prioritization.
• Define agent architecture including roles, handoffs, guardrails, and human-in-the-loop controls.
• Develop automated test frameworks for web, mobile, and API-based applications.
• Integrate AI-generated and agent-driven tests into CI/CD pipelines.
• Establish telemetry, metrics, and feedback loops for continuous improvement of test quality and coverage.
• Collaborate with senior leaders and product/program teams to define end-to-end test strategies aligned to customer journeys and business outcomes.
• Translate business requirements into structured inputs optimized for autonomous test generation.
• Prioritize features based on user experience, business impact, and testing risk.
• Ensure compliance with enterprise risk, control, and audit requirements.
• Establish guardrails, validation checkpoints, and escalation paths for agent-generated outputs.
• Perform root cause analysis on defects, test gaps, and automation failures and feed insights back into system design.

Should Have:

• Experience using LLMs or AI systems to generate test cases, scripts, or QA artifacts.
• Understanding of agentic AI patterns such as multi-agent collaboration, tool-using agents, human-in-the-loop validation, and self-healing or adaptive automation.
• Ability to evaluate and integrate AI tooling within enterprise constraints.

Skills:

• Java and Python.
• Test automation tools.
• Workfront Jira, Visio, PowerPoint, Excel.
• Agile methodologies and CI/CD understanding.

Qualification And Education:

• Bachelor’s degree in Computer Science, Engineering, Business, or related field.