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ServiceNowSanta Clara, us, Building A,B,C 2225 Lawson Lane
Software Engineering Manager (Omni Channel Management)
On-siteFull Time$166.5k - $291.4k per yearPosted 3 days ago
About the role
- 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
- 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
- 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 Benefits
- Generous family leave
- Matched donations
- Annual learning stipends
- Flexible PTO
- Competitive retirement plan
- Paid volunteer time
- A demonstrated track record of building, shipping, and operating production software, including hands-on delivery of AI-native application features that real users depend on rather than demos
- Direct experience authoring agentic instructions and prompts, designing AI-driven autonomous workflows, and building the evaluation and testing that verifies them, is required
- Typically requires a minimum of 8 years of related experience with a Bachelor’s degree; or 6 years and a Master’s degree
- Experience delivering conversational experiences in chat and voice,
- 5+ years of experience as a technical lead for technical teams
- Willingness to work directly with customers in a forward deployed capacity is required; prior forward deployed experience is an advantage
- Bachelor’s degree in Computer Science, Software Engineering, or a related technical field, or equivalent practical experience
- Advanced degrees or certifications are a plus but are not a substitute for a demonstrated record of shipping reliable AI-native applications
- Specification precision and architectural judgment. Ability to define problems rigorously enough that another engineer or an AI agent implements them correctly, and to decide soundly when to solve a problem in code, in instruction