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Were looking for a Senior Software Engineer to join a dynamic and high-impact team that owns the entire risk infrastructure behind our credit card. This includes real-time decisioning systems, integration with advanced ML models, risk engines, and credit strategies that directly impact our financial health and customer experience.
You'll collaborate closely with data scientists, backend developers, and product stakeholders to build systems from scratch, design complex architectures, and ensure scalable, high-performance infrastructure capable of making split-second decisions.
This is a unique opportunity to join a fast-growing fintech company, influence the product at its core, and shape the way credit and risk are managed across our platform.
Key Responsibilities:
Design, implement, and maintain large-scale backend systems for real-time risk and credit decisioning.
Build and optimize data pipelines and streaming systems that support our risk and ML models.
Work closely with data scientists to integrate predictive models into production.
Build microservices and internal tools that serve thousands of users and scale with company growth.
Own projects end-to-end from requirements and architecture to testing, deployment, and monitoring.
Collaborate with engineering and cross-functional stakeholders to ensure business alignment and smooth delivery.
Drive best practices in software engineering from code quality and security to performance and maintainability.
What Youll Bring:
A strong backend engineer with 7+ years of hands-on experience.
Experienced in designing and maintaining complex distributed systems.
Passionate about data and infrastructure: queues, stream processing, and data-centric microservices.
Excited to work on both product-oriented and infrastructure-oriented challenges.
Flexible, resourceful, and proactive.
Enjoy working closely with ML teams, learning new domains, and diving into unfamiliar territory when needed.

Required Quality Program Manager
Role Overview:
The Quality Program Manager will own the governance, enforcement, and continuous improvement of software quality across the engineering organization.
The role ensures that all products:
functional suitability - Meet requirements
Reliability - Work consistently
Usability - User experience standards
Performance efficiency - Run efficiently at scale
This position establishes company-wide quality standards, embeds them into engineering workflows, measures compliance, and collaborates with product, design, and infrastructure teams to ensure that every release meets the highest level of quality.
Key Responsibilities:
Governance & Standards
Define and maintain company-wide quality standards across the four pillars: functional suitability, reliability, usability, and performance efficiency.
Establish quality gates in CI/CD pipelines to enforce standards prior to release.
Ensure consistent application of quality practices across squads while enabling flexibility in implementation.
Enforcement & Compliance
Develop processes to measure and audit compliance with quality standards.
Collaborate with squad leads and guild heads to embed quality governance without introducing delivery bottlenecks.
Lead post-release and post-incident reviews to ensure quality gaps are identified and addressed.
Measurement & Reporting
Define and track quality KPIs, including:
Escaped defect rate and defect density
Test coverage and requirements coverage
Release readiness scores
Usability and accessibility compliance metrics
Performance KPIs (latency, throughput, error rate)
Provide reporting and insights to engineering leadership on quality health, risks, and trends.
Cross-Functional Collaboration
Work with Product Management to align quality thresholds with business requirements and release priorities.
Partner with Design to integrate usability and accessibility testing into the quality process.
Coordinate with Infrastructure teams to ensure automation, performance testing, and monitoring are embedded into pipelines.
Continuous Improvement
Drive initiatives to expand automated test coverage, improve release readiness, and strengthen user-facing quality validation.
Facilitate training and workshops to promote a quality-first mindset across engineering.
Introduce tools and practices that raise the bar for product quality.

Required Front End Engineer
What Youll Do:
As a Frontend Engineer on the Card Team, you will take ownership of the primary platforms our customers interact with daily: our web portal and native mobile app. You will be responsible for developing new features and enhancing the functionality related to our credit card services. This is a key role where you will directly shape the user experience for hundreds of thousands of cardholders, building the next generation of features for our rapidly growing product.
Key Responsibilities:
Develop, and maintain the customer-facing web and native applications for our credit card product.
Take ownership of the end-to-end development of new credit card-related features, from concept to deployment.
Implement new functionalities, such as customer benefits, rewards programs, and innovative payment solutions.
Collaborate closely with backend engineers to integrate APIs and deliver a seamless, high-performance user experience.
Write clean, efficient, and maintainable code, adhering to best practices and team standards.
Contribute to a collaborative environment, sharing your expertise and mentoring other team members.

Were looking for a hands-on Devops Team Lead to build, manage, and scale a high-impact DevOps team. Youll lead infrastructure strategy, promote DevOps excellence, and drive automation and platform reliability across the organization. This role combines technical leadership with team development and operational ownership.
Your Responsibilities & Impact:
Lead and mentor a team of 5 DevOps engineers.
Own the impact of our infrastructure on success by providing engineering autonomy.
Foster a culture of ownership, learning, and continuous improvement.
Grow and structure the team to support expanding infrastructure and business needs.
Infrastructure & Platform Ownership:
Own and evolve scalable, secure, and observable cloud architecture (with a focus on AWS).
Leverage Kubernetes (EKS), Terraform, and GitOps to maintain reproducible infrastructure.
Proactively identify needs that align with the product and business goals.
Take the lead on production issues, ensuring availability and timely response.
Improve CI/CD processes, developer experience, and automation pipelines.
Lead strategic projects to modernize infrastructure, adopt new technologies, and improve stability.
Proactively drive retrospectives, platform upgrades, and systemic reliability improvements.
Monitor infrastructure health, optimize cloud costs, and track infrastructure KPIs.
Deeply understand system complexity and internal service dependencies.
Partner with Security to maintain compliance (SOC 2, access control, audits).
Hands-On Execution - Actively contribute to the design and implementation.

Required Data Infrastructure Engineer
What Youll Do:
Design, implement, and enhance robust and scalable infrastructure that enables efficient deployment, monitoring, and management of machine learning models in production. In this role, you will bridge the gap between research and production environments, streamline data and feature pipelines, optimize model serving, and ensure governance and reproducibility across our ML lifecycle.
Responsibilities:
Decouple data prep from model training to accelerate experimentation and deployment
Build efficient data workflows with versioning, lineage, and optimized resource use (e.g., Snowflake, Dask, Airflow)
Develop reproducible training pipelines with MLflow, supporting GPU and distributed training
Automate and standardize model deployment with pre-deployment testing (E2E, dark mode)
Maintain a model repository with traceability, governance, and consistent metadata
Monitor model performance, detect drift, and trigger alerts across the ML lifecycle
Enable model comparison with A/B testing and continuous validation
Support infrastructure for deploying LLMs, embeddings, and advanced ML use cases
Manage a unified feature store with history, drift detection, and centralized feature/label tracking
Establish a single source of truth for features across research and production across research and production.

Required Data Engineer
As part of our Data Engineering team, you will not only build scalable data platforms but also directly enable portfolio growth by supporting new funding capabilities, loan sales and securitization, and improving cost efficiency through automated and trusted data flows that evolve our accounting processes.
Responsibilities:
Design and build data solutions that support our core business goals, from enabling capital market transactions (loan sales and securitization) to providing reliable insights for reducing the cost of capital.
Develop advanced data pipelines and analytics to support finance, accounting, and product growth initiatives.
Create ELT processes and SQL queries to bring data to the data warehouse and other data sources.
Develop data-driven finance products that accelerate funding capabilities and automate accounting reconciliations.
Own and evolve data lake pipelines, maintenance, schema management, and improvements.
Create new features from scratch, enhance existing features, and optimize existing functionality.
Collaborate with stakeholders across Finance, Product, Backend Engineering, and Data Science to align technical work with business outcomes.
Implement new tools and modern development approaches that improve both scalability and business agility.
Ensure adherence to coding best practices and development of reusable code.
Constantly monitor the data platform and make recommendations to enhance architecture, performance, and cost efficiency.

We are seeking an AI/ML Lead Engineer to join our R&D division and drive the adoption of advanced machine learning and AI solutions across our financial and operational domains. In this role, you will design and implement intelligent models that increase efficiency in collections and payments processing and build AI-driven tools that enhance call center performance and agent productivity.
We are looking for a hands-on, independent team player with strong foundations in data science, computer science, and backend engineering, combined with excellent analytical and algorithmic skills. This role is diverse and impactful, spanning machine learning development, data analysis, and backend engineering, with the opportunity to shape our AI/ML strategy for servicing and operations.
As part of the R&D group, you will work closely with engineers and product managers, leading and implementing AI/ML initiatives that directly align with our business goals and innovation vision.
Key Responsibilities:
Lead the design, development, and deployment of ML models to optimize collections and payments processing.
Develop and integrate AI-driven tools to improve call center efficiency and agent productivity.
Collaborate cross-functionally with engineers, product managers, and stakeholders to translate business needs into technical solutions.
Drive data analysis and modeling efforts, leveraging advanced algorithms to uncover insights and improve decision-making.
Ensure scalability, quality, and compliance of all AI/ML solutions within the financial and servicing domains.
Stay up to date with emerging AI/ML technologies and assess their potential impact on the companys strategy.
Mentor and guide team members, fostering knowledge-sharing and technical excellence.