Lead an engineering team within Oracle's AI-powered Development Experience organization. This role focuses on building capabilities that empower developers and agents to work more effectively, leveraging context, reusable tools, reliable execution, and constructive feedback.

As a Senior Software Development Manager, you will be responsible for your team's people management, execution efficiency, engineering quality, and operational achievements. You will collaborate with product management and senior technical leaders to translate organizational goals into a clear team roadmap, establish realistic delivery commitments, and guide features from their initial concept through to production deployment.

A key aspect of this role involves establishing AI-native workflows within your team. This includes adopting practices like spec-driven development, coding agents, agent loops, and workflow graphs. Success hinges on strong technical discernment, effective people leadership, and the ability to navigate and resolve ambiguity within your team's domain, while also coordinating across organizational boundaries to address dependencies and drive measurable improvements for developers.

Develop and nurture a high-performing engineering team by hiring, onboarding, coaching, and retaining talented individuals. Foster a team culture that champions experimentation, sound engineering judgment, accountability, and open communication regarding challenges.

Define and own team priorities and delivery, partnering with product management and technical leads to set clear outcomes and maintain an achievable roadmap. Translate ambiguous needs into well-defined problems and measurable acceptance criteria, developing delivery plans that account for technical uncertainties and dependencies.

Champion AI-native development practices, integrating AI into everyday engineering workflows from planning to maintenance. Guide the adoption of spec-driven development, agent loops, and workflow graphs, ensuring appropriate evaluation and human oversight. Establish ownership and maintenance practices for key AI assets like specifications, skills, and prompts.

Oversee technical quality and operations, partnering with technical leads on design decisions and ensuring robust testing, security, and observability. Manage the operational health of services, balancing feature delivery with maintenance and technical debt.

Drive the delivery of valuable capabilities and support their adoption by internal customers. Gather feedback and operational data to prioritize improvements, ensuring documentation and onboarding facilitate effective use.

Proven experience in managing software engineering teams, encompassing hiring, coaching, performance evaluations, and career development. A solid foundation in software engineering and a track record of delivering and operating production services or developer tools are essential.

Demonstrated ability to translate strategic priorities into focused team plans and successfully deliver projects amidst technical uncertainties and cross-team dependencies. Possess the technical judgment necessary to guide design discussions, assess risks, and collaborate effectively with senior engineers.

Practical experience applying AI to software development or delivering AI-enabled capabilities, with a strong understanding of evaluation methodologies and human oversight. Familiarity with AI-native development approaches such as spec-driven development, coding agents, agent loops, or workflow graphs is expected.

Experience in establishing engineering practices for testing, security, observability, and operational reliability is required. Excellent communication skills are crucial for resolving ambiguity, aligning stakeholders, and ensuring team accountability for results.