Software Engineering Manager Jobs in Nashville, TN

The Developer Tools space is evolving rapidly as advances in large language models (LLMs), AI agents, and intelligent automation create new possibilities for how software is designed, built, tested, deployed, and operated. Many of the most valuable problems in this space do not yet have established solutions, architectures, or even clearly defined requirements. Success in this role therefore requires a leader who is comfortable operating in highly ambiguous environments , can identify the right problems to solve, and can turn emerging technologies and loosely defined opportunities into a clear engineering strategy and executable roadmap.

As a Senior Manager, you will provide both organizational and technical leadership . You will build and develop a high-performing engineering team, establish priorities and operating mechanisms, and create clarity where requirements and technical approaches are still evolving. You will work closely with senior engineers, product managers, data scientists, AI/ML teams, and OCI service organizations to identify high-impact opportunities and take them from early exploration through architecture, production deployment, and broad adoption.

You will be expected to balance experimentation with disciplined execution—enabling teams to move quickly in a rapidly changing AI landscape while maintaining the engineering rigor, security, reliability, and operational excellence expected of OCI services.

• Build, lead, and develop a high-performing engineering organization , hiring and growing engineers and technical leaders while establishing a culture of ownership, technical excellence, collaboration, and customer focus.
• Create clarity from ambiguity by identifying high-value problems, defining engineering priorities, making informed tradeoffs with incomplete information, and translating broad opportunities in AI and developer productivity into actionable strategies and roadmaps.
• Define and drive the engineering strategy for AI-powered developer tools, platforms, and intelligent software development workflows , balancing near-term delivery with longer-term platform investments.
• Partner across product management, AI/ML, data science, platform engineering, and OCI service teams to establish shared priorities, influence technical direction, and drive complex initiatives across organizational boundaries.
• Provide strong technical leadership across distributed systems, cloud-native architectures, AI/LLM integration, developer platforms, data and evaluation systems , ensuring architectural decisions support scale, extensibility, security, and operational excellence.
• Establish mechanisms for rapid experimentation and learning, enabling teams to evaluate emerging AI technologies, validate hypotheses with developers, and make data-driven decisions about where to invest.
• Drive predictable execution across multiple concurrent initiatives, proactively identifying dependencies and risks, removing organizational and technical blockers, and holding teams accountable for measurable outcomes.
• Define success metrics for AI-powered developer experiences, including developer adoption, quality, productivity impact, reliability, latency, and cost efficiency, and use those signals to continuously refine strategy and priorities.
• Develop senior engineers and emerging leaders through coaching, delegation, technical sponsorship, and clear expectations, increasing the organization’s ability to operate independently and at scale.
• Represent the organization in architecture reviews, planning discussions, and leadership forums, communicating complex technical and organizational topics clearly and influencing decisions beyond the immediate team.

Required Qualifications

• 10+ years of software engineering experience , including experience designing and delivering complex production systems, with 3+ years of engineering management experience leading and developing software engineering teams.
• Demonstrated ability to lead through ambiguity , take ownership of loosely defined problem spaces, establish direction with incomplete information, and turn complex technical and business opportunities into executable engineering plans.
• Strong technical foundation in distributed systems, cloud-native architectures, developer platforms, or large-scale backend services , with the judgment to guide architecture, challenge technical assumptions, and make pragmatic engineering tradeoffs.
• Proven track record of building, developing, and retaining high-performing engineering teams , including coaching senior engineers, developing technical leaders, and creating strong ownership and accountability.
• Experience driving complex initiatives from early exploration and architecture through production delivery, operational maturity, and adoption , including managing dependencies and priorities across multiple teams.
• Strong understanding of AI/ML and LLM technologies and the opportunities and engineering challenges associated with applying them to developer productivity, automation, or intelligent software development experiences.

• BS or MS in Computer Science, Computer Engineering, or a related technical field, or equivalent practical experience.
  

Desired Qualifications

• Experience building AI-powered developer tools, intelligent development workflows, coding or engineering assistants, testing platforms, software delivery automation, or developer productivity systems .
• Practical understanding of LLMs, AI agents, retrieval and context techniques, model evaluation, AI inference systems, and emerging agentic development patterns , including the challenges involved in operating these technologies reliably in production.
• Experience building and operating platforms or services at public-cloud or large enterprise scale , with a strong understanding of reliability, observability, security, performance, and cost efficiency.
• Experience defining and using developer productivity, platform adoption, AI quality, or business-impact metrics to evaluate investments and guide engineering and product strategy.
• Track record of establishing new teams, technical charters, or platform capabilities in emerging problem spaces , successfully navigating uncertainty and taking ideas from experimentation to sustained production adoption.
  

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