Senior Manager - Software Engineering Management - AI Engineering

Responsibilities

• Build, grow, and maintain a high-performing, diverse team of IC2-IC5 engineers; hire and develop talent at all levels
• Set clear expectations for individual and team performance; establish metrics and goals aligned with business objectives
• Conduct regular 1:1s with direct reports; provide coaching, feedback, and career guidance tailored to each engineer's growth stage
• Create a culture of psychological safety, learning, and ownership; encourage experimentation and learning from failures
• Support engineers through career transitions—from IC2 to IC3, IC3 to IC4, and technical-to-management pathways
• Identify high-potential engineers and invest in their development; prepare emerging leaders for increased responsibility
• Address performance issues promptly and professionally; provide clear paths for improvement or transition
• Sponsor team members for growth opportunities, stretch assignments, and leadership development programs
• Celebrate wins and recognize contributions; foster a positive, collaborative team environment
• Model vulnerability, continuous learning, and AI-native thinking; lead by example in your own growth
• Define hiring strategy and conduct recruitment for open positions; build a pipeline of qualified candidates
• Lead technical interviews and assessments for engineering candidates at all IC levels; make hiring decisions
• Evaluate cultural fit and potential; hire for values and growth potential, not just current skills
• Onboard new engineers effectively; assign mentors and ensure smooth integration into the team
• Build a team with diverse backgrounds, experiences, and perspectives; actively work to improve representation
• Identify gaps in team capabilities (technical depth, domain expertise, AI/ML fluency) and address through hiring or development
• Participate in employer branding and represent the organization at recruiting events and universities
• Work with product, design, and cross-functional partners to define product roadmap and technical strategy aligned with business goals
• Establish technical direction for the team; make architecture and technology decisions that balance innovation, quality, and delivery
• Champion AI-native thinking across the team and organization; help teammates understand how to build with AI at the core
• Lead architectural reviews and technical decision-making; provide guidance on complex technical trade-offs
• Advocate for technical investments (refactoring, infrastructure, tooling) that improve team productivity and code quality
• Set quality standards for code, testing, and security; establish practices that enable sustainable delivery
• Partner with IC4/IC5 engineers to set multi-year technical roadmaps and long-term strategic initiatives
• Represent the engineering team in product and executive discussions; influence organizational priorities
• Drive team delivery of committed business objectives and product initiatives; maintain accountability for results
• Establish clear sprint goals, work-item prioritization, and delivery timelines; remove blockers for team success
• Conduct regular retrospectives; identify process improvements and drive adoption of better practices
• Manage team capacity; balance new feature development, technical debt reduction, and customer support
• Ensure team participation in on-call rotation; monitor incident response and post-incident learning
• Report on team progress, risks, and performance to senior leadership; provide transparent communication
• Escalate critical issues or resource constraints; collaborate with peer managers to solve cross-team dependencies
• Foster a culture of ownership where engineers take responsibility for quality, testing, and production outcomes
• Lead team through organizational changes and initiatives; maintain morale and focus during transitions
• Build and maintain relationships with key customers and stakeholders; understand their needs and priorities
• Participate in customer meetings, technical escalations, and business reviews; represent engineering capabilities and constraints
• Work closely with product management, customer success, and other teams; ensure alignment on priorities and capabilities
• Lead customer-critical incident response; ensure timely and professional resolution of critical issues
• Gather customer feedback and translate into product improvements; communicate back to customers how feedback is addressed
• Advocate for customers' needs within the engineering organization; ensure customer voice is heard in decision-making
• Build trust and credibility with customers through transparency, responsiveness, and technical leadership
• Participate in strategic customer discussions and technology roadmap reviews
• Model the organization's values and desired behaviors; set tone for engineering culture within your team and across teams
• Mentor junior managers or peers; contribute to manager development and leadership pipeline
• Participate in engineering leadership meetings; contribute to organizational strategy and policy
• Promote psychological safety, inclusion, and belonging; actively work to reduce barriers for underrepresented groups
• Foster knowledge sharing across the organization; encourage your team to contribute to brown bags, documentation, and communities
• Lead by example in work-life balance, continuous learning, and sustainable pace; prevent burnout
• Encourage your team to engage with the broader tech community (conferences, open source, speaking, writing)
• Develop deep understanding of AI/ML capabilities, limitations, and integration patterns; become a thought leader on AI-native development
• Coach your team on AI-native thinking—how to build systems with AI at the core, not as an afterthought
• Help engineers understand prompt engineering, retrieval systems, agentic workflows, and responsible AI principles
• Establish practices for evaluation-driven development, hallucination detection, and model performance monitoring
• Lead discussions on AI safety, data privacy, and responsible AI; ensure team builds with appropriate guardrails
• Create learning opportunities for the team to stay current with AI/ML advancements and frameworks
• Identify opportunities to apply AI to improve internal processes and team efficiency
• Contribute to organizational conversations about AI strategy and responsible AI practices
• Stay informed about LLM advancements, new models, and emerging techniques; share insights with your team

Qualifications

• 12+ years of professional software development experience, with 5+ years in AI-native systems, cloud-native architecture, or equivalent
• 4+ years of people management experience leading software engineers; track record of developing talent and building high-performing teams
• 3+ years managing application development on SaaS platforms (ServiceNow, Salesforce, or similar); deep understanding of platform architecture and constraints
• 3+ years hands-on experience with AI/ML systems, LLM integration, prompt engineering, and responsible AI practices
• Demonstrated expertise in hiring, team building, and organizational development; ability to attract and develop top talent
• Expert-level understanding of modern software engineering practices: CI/CD, testing, security, deployment
• Strong technical credibility; ability to engage in technical discussions with IC4/IC5 engineers; hands-on coding experience still valued
• Deep proficiency in Python, Java, and JavaScript; understanding of ServiceNow scripting and platform APIs
• Track record of delivering significant business results through engineering teams; ability to drive accountability and execution
• Experience scaling teams and organizations; demonstrated ability to work at multiple levels of complexity
• Exceptional communication and interpersonal skills; ability to influence across technical and non-technical stakeholders
• Strong coaching and mentoring skills; ability to develop engineers across all career stages
• Experience with Agile and Scrum methodologies; ability to adapt to team and organizational needs
• Demonstrated understanding of data security, compliance, and responsible AI practices
• Strong emotional intelligence; ability to navigate difficult conversations and build trust
• Experience with performance management, feedback delivery, and difficult personnel decisions
• Passion for building inclusive, psychologically safe teams where all engineers can thrive
• Bachelor's degree in computer science, engineering, business, or related field
• Experience leading teams through organizational change, technical migrations, or strategic initiatives
• MBA or management certification is a plus; however, demonstrated people leadership capability is more important
• Track record of developing talent into senior engineering leadership roles or managers
• Active engagement with engineering and AI/ML communities; thought leadership through speaking, writing, or open source is a plus
• Experience working with diverse teams and commitment to building inclusive organizations