Senior Engineering Manager, Mortgage
Leads the mortgage engineering organization, owning platform architecture, delivery, business-line outcomes, and team development. Requires senior engineering management experience, extensive software engineering experience, large-team leadership, business ownership, and expertise in scalable systems and AI.
About the job
Responsibilities
- Lead 16+ engineers as head of engineering for the mortgage business.
- Own the Mortgage platform’s technical roadmap, architecture, APIs, integrations, AI/ML-powered verification decisions, and customer experience.
- Partner with Product to shape product direction, build features, and improve existing functionality.
- Own delivery for the Mortgage business line and partner with business leadership on business results.
- Set technical direction, reduce technical debt, and scale architecture sustainably while maintaining delivery speed.
- Represent Engineering in strategy planning, including capacity modeling, headcount planning, and prioritization.
- Manage quality incidents as both technical and communications lead.
- Hire and develop engineering talent, mentor team members, and manage managers.
- Build customer relationships and drive results in partnership with them.
Requirements
- 8+ years of engineering management experience and 12+ years of overall engineering experience.
- Experience managing large teams, including managers.
- Experience owning a P&L or business line with revenue targets, capacity planning, and cross-functional accountability.
- Experience with products operating at scale in highly regulated environments, ideally mortgage lending.
- Deep understanding of service architecture, system design, and lean software development principles.
- Ability to make high-level prioritization decisions and balance technical and business tradeoffs.
- Strong written and verbal communication skills, including translating technical strategy for executives.
- Experience with machine learning and artificial intelligence.
- Demonstrated ownership, resilience, urgency, and ability to operate through ambiguity.
Compensation and Benefits
- On-target earnings or base salary: $269,000–$316,000 USD.
- Competitive cash and equity compensation.
- Learning and development allowance.
- Medical, dental, and vision coverage.
- Up to $25,000 reimbursement for fertility, adoption, and parental planning services.
- Flexible paid time off.
- Monthly wellness stipend.
- Expected to work from the office 3+ days per week.
Skills
Service Architecture, System Design, Lean Software Development, Machine Learning, Artificial Intelligence, APIs, Integrations, Capacity Planning, Headcount Planning, P&L Ownership, Mortgage Lending, Team Management
Similar jobs
Engineering Management jobs
Checkr
San Francisco, CA
Leads the Machine Learning Engineering team, setting technical strategy, developing engineers, and shipping reliable ML and agentic AI systems for product intelligence, fraud detection, and workforce integrity. Requires 10+ years building production software and ML/AI systems plus substantial engineering management experience.
Temporal
United States
Leads and grows a team building shared test systems and tooling for production-representative, workload, performance, and failure-mode validation. Requires engineering management experience, distributed-systems expertise, and a record of delivering widely adopted internal platforms.
United States
Leads machine learning engineering teams responsible for relevance, personalization, and video discovery systems serving Reddit’s core product. Requires 5+ years managing ML teams, hands-on experience with production ML systems, and strong recommender-systems expertise.
Headway
San Francisco, CALeads a team building retrieval and machine-learned ranking systems that match patients with therapists across a healthcare marketplace. Requires substantial engineering management experience, production software or ML expertise, and hands-on ownership of search, ranking, recommendation, or personalization systems.
Headway
New York, NYLeads two engineering teams responsible for outcomes measurement, patient segmentation, utilization, and network value systems. The role requires substantial engineering management experience, technical software engineering background, cross-functional leadership, and comfort with data- and ML-heavy products.