Ascenda Loyalty ★ 5.0

Great to Meet You! We are Ascenda

Ascenda powers the growth of leading financial services brands worldwide with premium rewards programs that differentiate their products, drive profitable customer behaviors, and create sustained engagement.

We are behind the world-class rewards propositions of major banks and fintechs around the globe, including brands like American Express, Capital One, Brex, Robinhood, Ramp, HSBC, Virgin Money (Australia), SMBC (Japan), ICBC (China), Bradesco (Brazil), ANZ (Australia), HDFC (India) and many others.

We are a thriving global Loyalty-as-a-Service company and are experiencing rapid expansion. Join our dynamic team contributing to the execution of our business strategies as we strive for hypergrowth. Our team spans 20 cities worldwide, with dual headquarters in Singapore and New York, totalling 270 team members.

Join us as a Senior DevOps Engineer for Data & ML Infrastructure in Vietnam or Singapore!

The Role

We are seeking an experienced Senior DevOps Engineer to join our Data Team and drive the reliability, scalability, and performance of our data and machine learning platforms. This role is critical to enabling our AI and data science teams to move fast and deliver innovative solutions while maintaining the integrity and efficiency of our infrastructure. You will lead the design and operation of robust ML infrastructure, collaborate with cross-functional teams, and champion best practices in DevOps and SRE for AI/ML systems at scale.

Your Impact

• Collaborate together with data engineers, data scientists, and AI engineers as a cross-disciplinary team to design, build, and maintain highly available and scalable infrastructure for data pipelines and machine learning workflows.
• Own and evolve the Site Reliability Engineering (SRE) practices for our data and AI/ML infrastructure, including monitoring, alerting, incident response, and performance tuning.
• Manage and optimize the deployment and lifecycle of ML workflows, including feature stores, model tracking systems (e.g., MLflow), and real-time recommendation services.
• Build and maintain CI/CD pipelines and infrastructure-as-code deployments for machine learning applications and data systems using Terraform, Kubernetes, Helm, and Ansible.
• Continuously improve automation, deployment speed, and system observability to support rapid experimentation and productionization of ML models
• Empower data engineers, data scientists, and AI engineers to be more self-sufficient by building intuitive tooling, documentation, and infrastructure abstractions for day-to-day operations and workflows
• Partner with teams to evaluate and integrate new tools and frameworks to streamline model development, deployment, and monitoring.
• Contribute to architectural decisions and strategic planning for the evolution of our data and ML infrastructure
  
  

Who You Are

• Strong knowledge in DevOps engineering with a focus on Linux-based cloud infrastructure, particularly AWS.
• Proficiency with infrastructure-as-code and automation tools such as Terraform, Kubernetes, Helm, Ansible, and CI/CD (we use Jenkins, Github Actions, ArgoCD).
• Hands-on experience building and operating AI/ML infrastructure, including ML workflows, feature stores, MLflow, and real-time ML-powered services e.g. recommendation engine.
• Solid understanding of Site Reliability Engineering (SRE) principles and their application to data and ML systems, in order to manage system performance metrics and SLA compliance.
• Experience with monitoring, observability, and incident management in distributed systems.
• Good DevOps scripting automation skills in languages such as Python, Ruby, and Bash.
• Excellent communication and collaboration skills; ability to partner effectively with cross-functional teams
• Good problem-solver, and able to work independently and manage multiple priorities.
• Experience with DataOps infrastructure is a strong plus, including Airflow or Argo Workflows, column-based data warehouse (we use AWS Redshift), and ETL/ELT pipelines.
• Familiarity with MLOps best practices and the evolving machine learning infrastructure ecosystem is another strong plus.
  
  

Why Join Ascenda?

Ascenda offers the unique opportunity to lead in LaaS, shaping the future of rewards programs. You'll be part of an environment that prizes groundbreaking ideas and their execution. We provide unparalleled career growth opportunities in a supportive and dynamic environment, complemented by a competitive compensation package that recognizes your impact.

Ascenda is dedicated to diversity and inclusion, welcoming candidates from all backgrounds. Join us on our mission to power the growth of the financial services industry by making loyalty simple and rewarding for everyone, everywhere.