Director of Engineering

LendingTree•Charlotte, NC

9d•$200,000 - $250,000•Hybrid

About The Position

LendingTree is hiring a Director of Engineering to lead a multi-team engineering organization responsible for our consumer-facing products and the platforms behind them. You'll own the engineering strategy, guide architecture and delivery across your portfolio, and you'll be accountable for the technical health, velocity, and reliability of everything your teams ship. This is a broad, highly cross-functional leadership role. You'll partner with Product, Design, Data Science, and Business stakeholders to shape the roadmap, and you'll be a senior voice on how we build — architecture, engineering standards, platform investment, and talent. Your portfolio will include ownership of the logged-in customer experience, our second- and third-party partner integrations, and the recommendation and personalization capabilities that shape what consumers see. Scope will flex over time with business priorities, so we're looking for a leader who can operate well across product areas rather than in a single lane. AI is a core part of this role on both sides of the equation: what we build and how we build it. You'll drive AI into the platforms and customer experiences your teams own — personalization, recommendations, assisted and conversational journeys — and you'll be one of the leaders shaping how our engineers work with AI day to day. Both come with accountability for adoption, quality, and measurable results. You'll lead through engineering managers and senior engineers, set technical direction, and stay close enough to the details to make good calls under ambiguity.

Requirements

10+ years of software engineering experience, including 5+ years in engineering leadership managing managers or multiple teams.
Proven experience owning consumer-facing product areas end to end, with accountability for both delivery and technical health.
Strong architectural judgment across distributed systems, APIs, and modern cloud environments — able to go deep with senior engineers and set direction.
Hands-on experience architecting and scaling integrations with external/third-party systems — APIs, partner platforms, or data feeds.
Experience partnering with Product, Design, and Data Science on personalization, recommendations, or other data-driven consumer features.
Experience shipping AI or ML-powered capabilities into a production, customer-facing product — including the platform work behind them (integration, evaluation, guardrails, monitoring).
Hands-on experience driving AI adoption inside an engineering organization — AI-assisted development tooling and agentic workflows — with a clear, evidence-based point of view on how AI changes engineering practice.
A track record of building and leading high-performing engineering teams, including hiring, coaching, and performance management.
Strong communication skills; comfortable representing engineering to executives and non-technical stakeholders.
Comfort operating with ambiguity and shifting priorities in a fast-moving business.

Nice To Haves

Experience in fintech, lending, insurance, or a two-sided marketplace product.
Experience leading both product engineering and platform/infrastructure teams.
Hands-on familiarity with modern AI development tooling and agentic coding workflows, and with LLM application patterns (RAG, evaluation, prompt and context engineering).
Experience defining governance, security, or quality standards for AI use in a regulated environment.
Familiarity with microservices, event-driven architecture, and modern CI/CD practices at scale.
Experience operating in a regulated environment (data privacy, PCI, GLBA, or similar).
Experience scaling an engineering organization through growth or re-org.

Responsibilities

Lead a multi-team engineering organization; own the roadmap, guide architecture, and delivery across your portfolio of consumer-facing products and platforms.
Set technical direction and engineering standards — architecture, code quality, testing, observability, and operational excellence — and raise the bar on craft and velocity.
Balance feature delivery against platform, tech debt, and reliability investment; make and defend those trade-offs with executive stakeholders.
Define and track the technical and experience metrics (uptime, latency, integration health, conversion, NPS/CSAT) that measure success for your portfolio.
Own the engineering strategy for embedding AI into the customer experiences your teams build — personalization, recommendations, assisted and conversational journeys, and intelligent automation across the consumer lifecycle.
Build the platform capabilities that make AI features viable at scale: model and LLM integration, retrieval and context pipelines, evaluation harnesses, guardrails, observability, and cost controls.
Partner with Product and Data Science to move AI capabilities from experiment to production — defining success metrics, evaluation criteria, and the path to full rollout.
Apply AI to make our partner integrations and internal platforms smarter — document and data extraction, decisioning support, and operational automation.
Own the responsible-AI posture for what your teams ship: accuracy, explainability, bias, consumer disclosure, and data handling, working with Compliance and Legal.
Own the logged-in customer experience: the account dashboard, offer and product management, and the ongoing engagement that keeps consumers coming back.
Drive the strategy and execution behind integrations with second- and third-party partners (lenders, servicers, data providers), ensuring they're secure, resilient, and easy to extend as the partner network grows.
Own the product recommendation experience end to end — how offers and next-best actions are surfaced, tested, and refined so each consumer sees the right thing at the right moment.
Partner with Product, Design, and Analytics to translate consumer insight into a roadmap that improves conversion, engagement, retention, and satisfaction across the full customer journey.
Hire, coach, and develop engineering managers and senior engineers; own performance management, career growth, and org design across your teams.
Represent engineering in cross-functional planning, budgeting, and prioritization, and communicate progress and risk clearly to senior leadership.
Partner with Security, Compliance, and Legal to ensure systems and consumer data handling meet regulatory requirements in financial services.