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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Lead Principal Platform Software Engineer - **Company:** Oracle - **Location:** Nashville, TN, United States - **Experience:** Expert - **Salary:** $96,800.0 - $306,400.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Mobile Application Development, Cloud Computing, Programming Tools, Oracle (Applications), Software Engineering, System Software, AI Coding Agents, Oracle Cloud Infrastructure - **Published:** October 23, 2026 - **Apply:** https://dejobs.org/x/x/577B57E2C2E346F7ABFBF0F4C121B38F/job/ ## About the Role * Extensive experience designing, delivering, and operating complex software systems or developer platforms. * Demonstrated technical leadership across multiple teams, with influence on architecture, engineering practices, and delivery beyond a single project. * A record of resolving ambiguous technical, project, and organizational challenges and delivering meaningful outcomes. * Strong hands-on engineering skills and the ability to move between architectural direction, implementation, and production troubleshooting. * Practical experience developing software with AI-native approaches, including spec-driven development, coding agents, agent loops, or workflow graphs. * Experience designing agent harnesses, context strategies, and evaluations, with an understanding of their effects on quality, reliability, and cost. * Strong judgment about security, operational reliability, and the appropriate balance of agent autonomy and human accountability. * Ability to communicate complex decisions clearly, build cross-team alignment, and lead through expertise and influence. Preferred qualifications * Experience building AI capabilities or developer tools adopted across a large engineering organization. * Experience with distributed agent execution, durable workflows, development environments, or coordinated changes across repositories. * Experience with reusable skills, MCP integrations, code intelligence, and access-aware context delivery. * Experience measuring developer and team productivity and using evidence to guide platform improvements. * Familiarity with OCI or comparable cloud infrastructure and enterprise software development environments. ## Description We are seeking a Lead Principal Engineer to help shape the technical direction of Oracle's AI-powered Development Experience organization. You will guide the capabilities and engineering practices that enable developers, teams, and agents to build, deliver, and maintain software more effectively. This is a hands-on individual contributor role with influence across teams and organizational boundaries. You will connect a broad technical vision to practical delivery, establish foundational architecture, and lead the adoption of AI-native development practices, including spec-driven development, agent loops, and workflow graphs. Your impact will come through both the systems you build and the engineering teams you enable. The role requires judgment and influence: identifying the right problems, creating clarity where requirements and ownership are uncertain, aligning stakeholders, and resolving technical, project, and organizational obstacles to delivery. You will partner with engineering and product leaders, security teams, and internal customers to translate emerging approaches into reliable capabilities with measurable benefits for developer and team productivity. Responsibilities Responsibilities Shape Oracle's AI-native development capabilities * Help define the technical vision and architecture for capabilities that support AI-native software development across Oracle. * Identify opportunities to improve developer and team productivity across planning, implementation, review, delivery, and maintenance. * Connect reusable platform capabilities-including agent execution, context, tools, skills, development environments, and evaluation-to useful developer experiences. * Make architectural and investment recommendations that balance near-term delivery with long-term reuse, reliability, security, and cost. Lead AI-native engineering practices * Establish and demonstrate practices that enable humans and agents to collaborate effectively throughout the software lifecycle. * Advance spec-driven development, translating intent, requirements, and constraints into specifications and executable acceptance criteria that guide implementation and validation. * Engineer agent loops and workflow graphs that coordinate planning, execution, feedback, and refinement, with appropriate state management, recovery, and human oversight. * Treat specifications, context, skills, harnesses, and evaluations as maintained engineering assets. * Apply these approaches within our organization and use delivery experience to guide broader adoption. Turn ambiguity into delivery * Lead initiatives where the problem, solution, ownership, or delivery path is initially unclear; establish a shared understanding and an actionable approach. * Resolve technical dependencies, competing priorities, and gaps between teams that impede delivery. * Align stakeholders on architectural boundaries, responsibilities, interfaces, and acceptance criteria. * Sequence complex initiatives into increments that test assumptions, deliver useful capabilities, and inform subsequent investment. * Remain accountable for technical outcomes through implementation, adoption, and operation. Build and validate foundational systems * Write foundational code, prototypes, and reference implementations that resolve uncertainty and establish patterns other teams can adopt. * Guide the development of agent harnesses and execution platforms that support secure, observable, and repeatable engineering work. * Enable workflows that move from a software-change requirement to validated, reviewable changes across affected repositories. * Establish evaluations and feedback mechanisms that assess correctness, security, maintainability, and successful task completion. * Use execution traces, failures, and developer feedback to improve specifications, context, orchestration, and tooling. Influence across teams and develop technical leadership * Build alignment across engineering, product, security, and service teams through sound judgment, clear communication, and demonstrated results. * Lead consequential design decisions and resolve disagreements while incorporating expertise from across the organization. * Mentor engineers and technical leads in AI-native development and the software engineering foundations needed to make it dependable. * Partner with internal customers to establish pilots, support adoption, and turn successful approaches into broadly reusable capabilities. * Contribute to hiring and strengthen the organization's technical depth. Demonstrate productivity and operational impact * Define success in terms of developer and team outcomes, including human effort, delivery time, accepted results, quality, and cost. * Evaluate complete workflows, accounting for review, correction, supervision, and operational effort. * Establish appropriate controls for agent permissions, execution isolation, traceability, and human intervention. * Use evidence to decide which capabilities to expand, improve, or retire.