Senior Director, Software Engineering – Capital Markets Technology

At Fannie Mae, the inspiring work we do helps make a home a possibility for millions of homeowners and renters. Every day offers compelling opportunities to impact the future of the housing industry while being part of a collaborative team thriving in an energizing environment. Here, you will grow your career and help create access to affordable housing finance.

Job Description

We’re looking for a forward looking, AI-first engineering leader to help shape the future of Capital Markets Technology at Fannie Mae. In this high-impact role, you’ll lead a 60+ person team to modernize mission-critical systems, drive Capital Markets platform transformation, and embed intelligence into every layer of our platform.

You’ll operate at the intersection of innovation, architecture, and people leadership, balancing enterprise-scale transformation with startup-style agility. If you’re passionate about building intelligent, resilient, and scalable systems that power the future of capital markets, this is your opportunity to lead that change.

Key Responsibilities

AI-First Technology Strategy

• Define and execute an AI-first engineering strategy that embeds intelligence across the technology stack from infrastructure to user experience.
• Strategically integrate AI/ML, GenAI & Agentic AI into products, user workflows, and research/decisioning.

Cloud & Platform Modernization

• Lead Capital Markets platform transformation with AI-first principles, cloud-native, API-driven, event-based, and microservices-oriented architectures using AWS.
• Drive adoption of AWS-native services (e.g., Lambda, ECS, S3, RDS), infrastructure-as-code (Terraform), and CI/CD pipelines (GitLab).
• Ensure scalable, secure, and maintainable design patterns while managing technical debt and long-term platform health.

Startup-Style Innovation & Product Thinking

• Operate with a product-first mindset, aligning engineering with customer needs and business outcomes.
• Rapidly prototype and iterate on new ideas using AI and emerging technologies.
• Lead innovation initiatives such as hackathons, proof-of-concepts, and strategic partnerships with mortgage technology companies and AI vendors.

Engineering Leadership & Talent Development

• Build, scale, and mentor a high-performing engineering organization focused on AI fluency, cloud-native skills, and continuous learning.
• Foster a culture of innovation, inclusion, psychological safety, and technical excellence.
• Develop leadership programs and career frameworks to grow future-ready engineering talent.

Operational Excellence & Post-Production Ownership

• Drive measurable improvements in system reliability, deployment velocity, and AI model performance through engineering excellence and operational rigor.
• Establish and enforce engineering standards, architectural governance, and KPIs.
• Ensure teams own their software end-to-end from deployment to monitoring, incident response, and continuous improvement.
• Implement robust observability practices (e.g., logging, tracing, metrics) to proactively detect and resolve production issues.
• Lead post-incident reviews and root cause analysis to drive systemic improvements.
• Ensure compliance with security, regulatory, and risk management requirements, especially in AI and data privacy contexts.

Cross-Functional Collaboration

• Act as a strategic partner to business, product, architecture, and infrastructure teams.
• Represent engineering in leadership forums and steering committees.
• Translate complex technical and AI concepts into clear, actionable insights for junior associates and non-technical stakeholders

Qualifications

Required Experience

• 8 years of experience in Software Engineering and in senior leadership roles
• Proven success leading large-scale engineering teams in a cloud-native.
• Experience modernizing legacy systems and driving digital transformation, regulated industry experience would be a plus
• Deep expertise in Java, Spring Boot, GitLab, Terraform, and AWS (ex. Serverless, Containers, Lambda, S3, RDS).
• Strong understanding of microservices, API ecosystems, event-driven architecture, serverless architecture and DevSecOps.
• Demonstrated success integrating AI/ML and GenAI into enterprise-grade applications.
• Familiarity with full-stack development and modern frameworks (e.g., Angular/React, Java, Springboot, Python).
• Exceptional executive presence, communication, and stakeholder management skills.
• Strategic thinker with a strong bias fo