Role Summary:
As an Engineering Leader, you will provide technical and people leadership for teams delivering complex software products and platforms. You will partner with architects, product leaders, and engineering teams to define technology strategy, guide solution delivery, and ensure successful execution of cloud-native solutions on AWS. This role requires a strong blend of engineering leadership, organizational development, operational excellence, and AI-enabled innovation.
Key Responsibilities:
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.
- Strengthening 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 & 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 & 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
- 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.