Lead ML Ops/DevOps Engineer - AI Engineering

The Opportunity

As a Lead MLOps/DevOps Engineer on our Generative AI team, you’ll be at the cutting edge of language model applications, building innovative solutions across key areas of the FICO platform—including fraud detection, decision automation, workflow orchestration, and system optimization and also internal productivity. You will deploy production systems, troubleshoot operational issues, and integrate services at scale. You’ll have the opportunity to make a measurable impact by bringing next-generation AI capabilities into production, collaborating with a world-class team to build robust, scalable infrastructure and accelerate innovation across FICO’s platform. 

What You’ll Contribute

• Design, build, and maintain scalable, resilient data and ML pipelines, infrastructure, and workflows using tools such as Terraform, GitHub Actions, ArgoCD, Helm, and others. 

• Automate infrastructure provisioning and configuration management using cloud-native services (preferably AWS) with tools like Terraform, CloudFormation. 

• Design, containerize, and manage Kubernetes (EKS) clusters and/or ECS environments in AWS. Collaborate with development teams to optimize performance, deployment, and cost. 

• Partner with DevOps and SRE teams to ensure high availability, observability, scalability, and security of the data and ML infrastructure. 

• Work closely with Data Scientists and ML Engineers to operationalize machine learning models, including building CI/CD pipelines for model training, validation, and deployment. 

• Implement observability for data pipelines and ML services using tools like Prometheus, Grafana, Datadog, or similar. 

• Develop and maintain automated pipelines for model retraining, monitoring drift, and versioning in production. 

• Support experimentation and prototyping in areas such as Machine Learning and Generative AI, transitioning successful prototypes into production systems. 

• Ensure cloud infrastructure is secure, compliant, and cost-efficient, following best practices in governance, identity, and access management. 

What We’re Seeking 

• 8+ years of experience in DataOps, MLOps, or related fields, with 3+ years focused on ML model operationalization and workflow automation.

• Proficient in AWS services including EC2, S3, IAM, ACM, Route 53, CloudWatch, EKS, and ECS.

• Experience with infrastructure as code (IaC) tools such as Terraform, CloudFormation, and Helm.

• Familiarity with CI/CD for ML pipelines, GitOps practices, and tools like GitHub Actions, Jenkins, or Argo Workflows.

• Strong scripting and automation skills using Python, or GitHub workflows. 

• Solid understanding of observability and monitoring tools (e.g., Prometheus, Grafana, Datadog, or OpenTelemetry). 

• Solid understanding of security best practices for cloud and Kubernetes environments, including secrets management, identity & access control, and policy enforcement.

• Strong understanding with data governance, lineage, and metadata management is a plus.

• Excellent collaboration and communication skills, with a proven ability to work effectively in cross-functional, globally distributed teams.

• A bachelor’s degree in computer sciences, or a related discipline, or equivalent hands-on industry experience. 

Our Offer to You

 

• An inclusive culture strongly reflecting our core values:  Act Like an Owner, Delight Our Customers and Earn the Respect of Others.

• The opportunity to make an impact and develop professionally by leveraging your unique strengths and participating in valuable learning experiences.

• Highly competitive compensation, benefits and rewards programs that encourage you to bring your best every day and be recognized for doing so.

• An engaging, people-first work environment offering work/life balance, employee resource groups, and social events to promote interaction and camaraderie.

• The targeted base pay range for this role is: $140,000 to $220,000 with this range reflecting differences in candidate knowledge, skills and experience.
   

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