Development Manager -Residential Mortgage Valuations Technology - Remote

What You'll Do Team Leadership & Delivery

• Own end-to-end delivery for a team of 10 across development and QA — setting standards, removing blockers, and holding the bar on quality and timelines.
• Run lean, pragmatic Agile delivery: sprint planning, backlog grooming, dependency management, and proactive risk escalation.
• Be a visible technical presence — writing code, reviewing PRs, and pairing with engineers to move them forward, not just directing from a distance.
• Mentor engineers at varying skill levels; build a culture where the team holds each other accountable and grows together.
• Plan, prioritize, and allocate resources across multiple concurrent projects, balancing deadlines with quality standards.
• Oversee the creation and maintenance of technical documentation standards — and ensure they are actually followed.

• Set and enforce development standards across Python and .NET codebases — code quality, testing discipline, security, and performance.
• Architect and guide integration of Python-based analytical tools with enterprise .NET systems via APIs and shared data infrastructure.
• Lead the team's adoption of AWS services for deployment, scalability, security, and operational reliability.
• Evaluate and implement AI/ML tooling to improve developer productivity and automate routine tasks.
• Ensure rigorous testing and debugging processes to deliver reliable, scalable software products.
• Drive innovation and continuous improvement in development practices and technology adoption.

• Work directly with quantitative analysts, valuations professionals, and business leaders who have high technical fluency — speak their language and earn their trust.
• Translate business requirements from mortgage valuation workflows into clear technical specifications.
• Demonstrate what "good" looks like in software delivery to business stakeholders who may be sophisticated coders but less familiar with engineering discipline and SDLC best practices.
• Communicate project status, risks, and tradeoffs clearly to leadership — no surprises.
• Collaborate with stakeholders to define product requirements and drive innovation aligned with business goals.

• 12+ years of software development experience, with at least 3–5 years in a technical leadership or engineering management role.
• Hands‑on Python proficiency — you can write it, review it, and raise the bar on it. This is non‑negotiable; the business community this team serves runs on Python.
• Bachelor's degree in Computer Science, Engineering, Information Systems, or an equivalent combination of education and experience.
• Solid working knowledge of .NET/C# — sufficient to oversee architecture decisions and conduct meaningful code reviews.
• Experience managing full delivery cycles: planning, resourcing, shipping, and iterating.
• Demonstrated ability to work with technically sophisticated non‑engineering stakeholders.
• Track record of coaching and developing engineers — not just managing throughput.
• AWS experience: services, deployment patterns, security best practices.
• Fluency with modern Dev Ops tooling:
  Azure Dev Ops, Git, CI/CD pipelines, Jira or equivalent.
• Strong grasp of OOP principles, API design, RESTful web services, and application integration patterns.
• Excellent written and verbal communication skills; comfort presenting to senior leadership.

• Experience in financial services, particularly residential mortgage, valuations, or related quantitative domains.
• Familiarity with residential mortgage analytics and valuation platforms — experience with tools such as Andrew Davidson (ADCo), Intex, Poly Paths, Bloomberg, or CompassPoint is a strong differentiator; exposure to cashflow engines, pricing engines, or CAS (Collateral Analysis System) is a plus.
• Understanding of how industry valuation tools integrate with or inform the software systems your team will build and maintain.
• Familiarity with structured and unstructured data at scale; experience with API design and integration patterns for rapidly evolving products.
• Exposure to AI/ML tooling in a development context — using it to accelerate delivery, not just theorize about…