About the RoleAs a Senior Backend Engineer on the Document Verification (DocV) team, you'll build and refine the critical server-side components that enable identity verification at scale. This includes developing the core microservices and APIs that drive document capture, processing, and verification workflows - including integration with machine learning models for ID authenticity and fraud detection. Your work will ensure millions of users can verify their identities seamlessly on our platform, reinforcing Socure's reputation for trustworthiness, speed, and security.
Responsibilities- Develop and maintain scalable backend services: Build and maintain robust, scalable, and secure backend services and APIs for identity document processing and verification . Ensure these services are reliable and performant to handle high-volume identity verification requests.
- Cross-functional collaboration: Collaborate with Product, Data Science/Machine Learning, and Infrastructure teams to design and implement new document verification features in an agile environment . Work together to translate product requirements and ML model outputs into efficient backend solutions.
- Improve code quality and practices: Drive improvements in code quality, testing coverage, performance optimization, security, and CI/CD practices for the DocV backend systems. Champion best practices in coding, code review, and deployment to enhance reliability and maintainability.
- Own backend architecture: Own backend architecture decisions and advocate for best practices in API design, microservice architecture, and secure data handling across the team. Ensure the system is designed for scalability, resilience, and ease of integration with other Socure services.
- Optimize performance and reliability: Analyze production metrics and real-world usage data to continuously refine system performance, reliability, and scalability. Proactively identify bottlenecks or failure points and drive initiatives to optimize response times and uptime.
- Integrate ML/CV capabilities: Contribute to the integration of machine learning and computer vision components into the DocV backend pipeline, ensuring smooth deployment of document verification models and algorithms . Work closely with data scientists to incorporate model outputs (e.g. OCR results, face match scores) into backend decisioning logic.
- Collaborate with frontend/mobile teams: Work closely with frontend and mobile engineers to define clear API contracts and ensure a seamless end-to-end user experience across web and mobile SDKs. Provide support and guidance to client-side teams in using backend services effectively and debug integration issues when necessary.
Qualifications- Experience: 5+ years of experience building and shipping modern backend services or distributed systems at scale. Proven track record of delivering production backend software in fast-paced environments.
- Programming skills: Advanced proficiency in backend programming languages (e.g.,GoLang, Java, Scala) and frameworks for building APIs and microservices . Hands-on experience with developing gRPC and RESTful APIs and server-side business logic.
- Scalable systems expertise: Experience building scalable, high-availability microservices and RESTful APIs that can handle large volumes of transactions . Familiarity with designing for fault tolerance and low latency in a cloud environment.
- Performance & security: Solid understanding of performance optimization and backend security best practices, especially when processing sensitive data (PII). Ability to profile services, optimize database queries, and implement measures to secure data in transit and at rest.
- Team collaboration: Proven ability to collaborate effectively with cross-functional teams including frontend engineers, data scientists, and product stakeholders. Excellent communication skills to articulate technical concepts and requirements across disciplines.
Preferred Qualifications- Domain knowledge: Experience with identity verification, fraud prevention, or related domains (e.g. Document Verification, Device Risk, Identity Verification) is a strong plus. Familiarity with document verification workflows or fraud risk scoring will help you hit the ground running.
- ML/CV integration: Familiarity with computer vision or machine learning techniques in the context of document verification (e.g., OCR, face matching). Experience deploying or integrating ML models into backend services is a plus .
- Cloud and data processing: Knowledge of AWS cloud platform (Experience with GCP is a plus) and container orchestration (Docker/Kubernetes) for deploying services. Familiarity with streaming and data processing frameworks (e.g., Kafka, Spark) for building high-volume data pipelines is a plus .
Continuous improvement: Passion for continuous improvement in backend architecture, code quality, and engineering best practices. Enthusiasm for evaluating new technologies and techniques to enhance the DocV platform's performance and reliability.
