Manager, Software Engineering Omni Channel Management

Overview

As the Manager of Software Engineering, you will lead the OmniChannel team within Customer Support Management (CSM). This hands-on leadership role will set technical direction, driving execution of key initiatives such as Voice AI, Chat AI, Contact Center Integrations among other Omni Channel capabilities. In addition you will also oversee engineering operations, ensure product quality and scalability, and foster collaboration across global teams.

About the Role: 

As a Manager, Software Engineering Management, you will set technical direction and serve as a thought partner to your engineers and product counterparts, staying close enough to the work to make sound technical judgments and unblock your team when it matters. You will lead a team as a people manager, investing in their growth deliberately, raising the performance bar with intention rather than simply maintaining it, and consistently creating space for innovation alongside a fast-moving technical growth.  

What you get to do in this role:  

• Manage product development activities and oversee end-to-end engineering deliverables. 
• Manage and build a team of engineers by identifying individual strengths, providing career development, and proactively elevating engineers. 
• Manage daily activities and lead monthly release cycles with product management, providing technical feedback to maintain delivery velocity, ensuring engineering excellence and code quality.
• Design conversational experiences across chat and voice. Build experiences that hold context across turns, hand off cleanly between automated and human agents, and behave consistently across channels — accounting for what voice imposes: latency budgets, barge-in, speech recognition error, disambiguation, and confirmation before consequential actions.
• Build AI native applications. Design and ship applications built around agentic behavior — intent interpretation, multi-step reasoning, tool invocation, and action on the user's behalf — together with the data models, integrations, and channels that make them usable in production.
• Design AI-driven autonomous workflows. Decompose business processes into the steps and decision points an agent can execute — determining where autonomy is appropriate, where a human checkpoint is required, and how exceptions, retries, and hand-back to a person are handled.
• Build automated evaluation and test non-deterministic behavior. Design and operate the evaluation that makes change safe — golden datasets, multi-turn conversation suites, model-as-judge scoring calibrated to human review, CI gates, and drift detection — plus adversarial, jailbreak, grounding, and tool-selection testing.
• Specify precisely and direct AI coding agents. Convert requirements into testable specifications with explicit scope, constraints, and acceptance criteria; decompose work into agent-sized tasks; and review agent output for correctness and maintainability. You own the result regardless of what produced it.
• Own quality, safety, and reliability in production. Monitor conversation quality, containment, hallucination, and unsafe actions; defend against prompt injection and data leakage; and feed production failures back into specifications and evaluation sets.
• Collaborate across product, design, and engineering. Partner with product managers, designers, conversation designers, and engineers to define success criteria, align on tradeoffs, and communicate capability and risk clearly.
• Solve ambiguous problems and fast-changing priorities by providing clear direction to the team by fostering collaboration and applying structured decision-making.

Department: Engineering, Infrastructure and Operations
Function: Engineering
Experience Level: Not Applicable