Title: Head of Engineering
Compensation: 200-275K Base only
No C2C, no sponsorship, No 3rd party agencies please
Client is re-writing the risk model for the non-QM mortgage market -combining data analytics, proprietary risk intelligence, and Loan Defect Insurance to turn mortgage manufacturing risk into quantifiable, insurable outcomes for lenders, investors, and RMBS issuers. Client (CLIENT) is the analytical engine powering this platform, built on neural network triage, hazard-based pricing, and AI-driven defect detection. The Head of Engineering will take CLIENT from its current state to an institutional-grade production system that counterparties and reinsurers can trust, integrate with and audit.
In this role you will:
Own CLIENT's full technical architecture -cloud environment, data warehouse, pipeline orchestration, model serving, and security controls
Build and lead CLIENT's engineering team, defining the hiring roadmap, transitioning from external contractors to a full-time team over time, and managing developers and vendors against clear delivery milestones."
Implement multi-client RBAC ensuring complete data segregation across institutional counterparty workloads Build and maintain CLIENT's MLOps infrastructure: CI/CD pipelines, model versioning, automated retraining, rollback capabilities, and production drift monitoring
Own the API layer and counterparty-facing technical interfaces versioned model output delivery, institutional SLA commitments, and onboarding documentation
Own model governance infrastructure: audit trails, documentation standards, and reproducibility tooling
Design and maintain disaster recovery and business continuity procedures - RTO/RPO targets, failover testing, and documentation for counterparty due diligence The Ideal Candidate:
Builds for auditability and institutional trust, not just functionality Thrives in a zero-to-one environment -hands-on when needed, strategic when it counts
Communicates architecture decisions clearly to non-technical stakeholders
Basic Qualifications:
8+ years of software or data engineering experience, with at least 3 years leading production ML or data platforms
Cloud-native architecture experience: data warehouses, pipeline orchestration, and model serving
Hands-on MLOps: CI/CD for ML, model registries, feature stores, production monitoring
Experience implementing multi-client RBAC and data segregation at scale
Preferred Qualifications:
Familiarity with SR 11-7 or equivalent model risk management frameworks
Platforms subject to external audit or counterparty due diligence in financial services or insurance
DR/BCP design for platforms processing sensitive financial data
Tech: AWS or GCP Snowflake / dbt Airflow or Prefect MLflow Docker / Kubernetes Terraform FastAPI GitHub Actions
