Engineering Leader

The core responsibilities for the job include the following:

Engineering Leadership:

• Lead, coach, and develop multiple teams of software engineers and technical leads.
• Lead, coach, and inspire high-performing teams of software engineers, technical leads, and engineering managers to deliver exceptional business outcomes.
• Foster a culture of innovation, accountability, continuous improvement, inclusion, and customer obsession.
• Build, develop, and retain top engineering talent through effective hiring, mentoring, performance management, and career development.
• Strengthen engineering and technical leadership capabilities across modern software engineering, cloud-native technologies, AI, and agentic systems.
• Create and sustain scalable, high-performing, AI-ready engineering organizations that embrace learning, experimentation, and operational excellence.
• Lead talent planning processes, including performance reviews, compensation planning, succession planning, and leadership development.
• Drive organizational effectiveness through strategic workforce planning, skills development, and capability-building initiatives.
• Cultivate an inclusive, diverse, and collaborative team environment that reflects Delta's values of care, integrity, resilience, and servant leadership.
• Attract, develop, and empower world-class engineering talent while fostering engagement, retention, and long-term career growth.
• Serve as a trusted leader and coach, enabling teams to navigate change, adopt emerging technologies, and deliver measurable business impact.

Product and Delivery Leadership:

• Own end-to-end delivery of strategic technology initiatives and customer-facing applications.
• Partner with product managers and business leaders to define roadmaps and execution strategies.
• Drive Agile and DevOps practices to improve speed, quality, and predictability of delivery.
• Manage program risks, dependencies, capacity planning, and stakeholder communications.
• Ensure achievement of business outcomes through measurable engineering execution.
• Manage engineering capacity, prioritization, and investment decisions aligned to business objectives.
• Communicate roadmap progress, risks, and outcomes to senior leadership and stakeholders.
• Partner with Product, Security, Architecture, and Enterprise Platform teams to deliver strategic initiatives.

Technical Leadership:

• Guide architecture, design reviews, and technology decisions.
• Lead development of cloud-native, microservices-based, event-driven applications.
• Champion engineering excellence, automation, observability, reliability, and security.
• Establish best practices for scalable, resilient, and secure software development.
• Drive adoption of platform engineering and developer productivity initiatives.

AI and Agentic Engineering Leadership:

• Drive implementation of AI-assisted software development using tools such as GitHub Copilot, Claude, and similar coding assistants.
• Partner with data science and AI teams to integrate generative AI, ML, and agentic AI capabilities into products and engineering workflows.
• Lead teams building AI-powered agents capable of autonomous reasoning, task execution, workflow orchestration, and decision support.
• Promote design patterns leveraging Large Language Models (LLMs), Retrieval Augmented Generation (RAG), Agentic Workflows, Model Context Protocol (MCP), Multi-Agent Systems, and AI Orchestration Frameworks
• Establish governance and quality standards for AI-generated code and AI-enabled applications.
• Drive measurable improvements in engineering productivity through AI-enabled SDLC processes.

Operational Excellence:

• Establish engineering KPIs, SLOs, and platform health metrics.
• Improve reliability, availability, performance, and scalability of applications.
• Leverage AIOps and intelligent observability platforms to reduce incidents and improve operational outcomes.
• Lead incident response, root-cause analysis, and continuous improvement initiatives.

Requirements:

• Bachelor's degree in computer science, engineering, information technology, or a related field.
• 14+ years of progressive software engineering experience with at least 5+ years leading engineering teams and people managers.
• Demonstrated success building, scaling, and developing high-performing engineering organizations.
• Proven experience delivering enterprise-scale distributed systems and customer-facing applications.
• Experience driving adoption of AI-assisted software development tools such as GitHub Copilot, Claude, Cursor, or similar platforms.
• Understanding of agentic AI concepts, including AI agents, orchestration frameworks, RAG architectures, and Model Context Protocol (MCP).
• Experience leading teams that develop or integrate generative AI and agentic AI capabilities into enterprise applications.
• Strong experience with cloud platforms (AWS preferred).
• Experience leading Agile product and engineering organizations.
• Strong stakeholder management and executive communication skills
• Experience driving organizational change and technology modernization initiatives.

Preferred qualifications:

• Master's degree in computer science, engineering, or a related field.
• Experience working in an airline technology environment is preferred.
• Experience managing globally distributed engineering teams.
• Hands-on experience with generative AI, AI platforms, and machine learning solutions.
• Experience implementing platform engineering and internal developer platforms.
• AWS certifications or cloud architecture certifications.
• Experience with Site Reliability Engineering (SRE) practices.
• Experience driving enterprise AI adoption programs.

Skills

AI, AWS, Copilot, LLM, MCP, RAG, cloud, engineering, software