Role Overview:
We are seeking a Lead Technical Product Engineer (TPE) to shape the next generation of digital experiences across Delta.com. This role is designed for engineers who combine deep software engineering expertise with product thinking to translate complex customer problems into scalable, enterprise-grade technical solutions. As a technical leader, you will drive the end-to-end product lifecycle, partner closely with Business Product Owners, UX Designers, Architects, and Engineering teams, and influence architectural decisions, platform modernization, and engineering excellence across the platform. You will leverage modern AI technologies, agentic workflows, and distributed systems to accelerate product delivery, improve developer productivity, and create intelligent, customer-centric experiences while serving as the trusted technical bridge between business and engineering.
Responsibilities include, but are not limited to:
- Technical Leadership & Architecture: Act as the technical product leader for the engineering organization, bridging customer needs with engineering execution. Translate business challenges into scalable technical architectures, influence engineering standards, facilitate architecture reviews, guide API and platform design, drive technology modernization, and balance technical trade-offs to deliver secure, scalable, and high-performing digital experiences.
- Delivery & Execution: Translate business strategy into technically executable roadmaps, Epics, APIs, system capabilities, and engineering initiatives. Partner with Product Managers to decompose complex technical initiatives into incremental, value-driven deliveries while maintaining architectural integrity.
- AI-Driven Product Innovation: Design, prototype, and productionize AI-powered capabilities using modern GenAI technologies including LLMs, Retrieval-Augmented Generation (RAG), Model Context Protocol (MCP), agentic architectures, orchestration frameworks, and enterprise governance to improve both customer experiences and engineering productivity.
- Product Strategy & Roadmap Ownership: Define and own the technical product vision. Apply system thinking to ensure day-to-day feature development aligns with the long-term roadmap and broader digital platform strategies along with building customer insights
- Strategic Trade-off Analysis: Balance speed-to-market with the need for scalable architecture. Make rigorous, ROI-driven decisions to prioritize initiatives that maximize business value and elevate the digital customer experience.
- Customer-Centric Discovery: Drive engineering decisions through customer outcomes and measurable business impact. Continuously evaluate user journeys and leverage customer empathy to ensure technical solutions are solving genuine pain points rather than just shipping features.
- Resiliency & System Health: Apply Site Reliability Engineering metrics (SLAs, SLOs) and build self-healing systems, including graceful degradation patterns, system monitoring, telemetry, dashboards, and reporting standards. Proactively identify and resolve technical risks, bottlenecks, and dependencies during the development cycle.
- Responsible AI & Governance: Ensure AI-powered solutions are secure, explainable, observable, cost-efficient, and compliant with enterprise governance standards while continuously evaluating model quality, reliability, and business outcomes.
- Data-Driven Triage & Optimization: Lead root cause analysis of production issues, actively digging into browser console errors, performance degradation reports, and network traces to diagnose live bugs, and identify immediate fixes and preventative steps. Leverage web & system analytics, such as Adobe Analytics, Quantum Metrics or Dynatrace/Sumologic logs, and system health tools to analyze customer pain points, estimating and validating solution impacts.
- UI/UX Integration: Partner closely with UI/UX teams to capture interactive needs, defining precise acceptance criteria based on component layouts, user states, and design systems. Author detailed technical requirements mapping front-end user actions to downstream middleware services, orchestrating field-level validations and payload schemas.
- Engineering Productivity: Keep abreast with Agile/Scrum best practices and new trends. Drive adoption of AI-assisted software engineering practices, including intelligent coding assistants, AI agents, automated code generation, test generation, documentation, code reviews, and developer workflows to improve engineering productivity.
