About Louisa AI
Louisa AI, a cutting-edge institutional revenue enablement platform, was originally developed at Goldman Sachs and became an independent entity in 2023. It utilizes AI to maximize revenues by mapping the expertise and relationships within organizations, primarily serving financial institutions. Louisa AI emphasizes connecting people through AI, not replacing them, leveraging relationship graphs and news integration to enhance revenue generation and connections based on expertise, relationships, and relevant information.
Responsibilities:
As a DevOps engineer on the Louisa team, you will have the opportunity to:
- Build and Release Management:
- Architect and create an effective build and release process using industry best practices and tools. Create and manage build scripts to deploy software in a multi-cloud environment.
- Look for opportunities to automate as much of the deployment process as possible to provide for repeatability, auditability, scalability and build in process enforcement.
- Implement Continuous Integration (CI) practices to drive development teams to implement smaller changes and commit code to the version control repo frequently.
- Implement Continuous Development (CD) practices that automates deployment of the application to several environments – Dev, Test and Production.
- Cloud Infrastructure Engineering:
- Build, configure, and support infrastructure at cloud scale using AWS.
- Create and automate all container-based client applications, orchestration, and auto scaling and cross-availability zone failover for the ecosystem, leveraging ECS Fargate, Kubernetes or similar tools.
- Site Reliability Practice:
- Manage production outages, both working to resolve the outage as well as root-cause the problem and provide long-term resolution or early identification strategies, as well as ensure we are able to deliver efficiently and effectively to our users by optimizing developer processes and the developer experience, in addition to ensuring that applications are resilient and meet SLAs.
Minimum Qualifications:
- Bachelor’s degree in computer science or engineering, or equivalent practical experience.
- 5+ years of consumer-facing product experience which includes deploying, maintaining, and managing cloud-based applications.
- Hands-on Experience in container management framework Deployment, Orchestration using Kubernetes and helm.
- Hands-on experience with Infrastructure As Code Tools like terraform and terragrunt.
- Excellent troubleshooting and problem solving skills.
- Knowledge of IP networking, VPN’s, DNS, load balancing and/or firewalls.
- Proficiency in managing systems within multiple sites including fail-over redundancy & auto scaling (knowledge of best practices and IT operations in an always-up, always-available service).
- Strong Experience with Amazon Web Services like Route53, VPCs, EC2, ELB, CloudFront, ECS, RDS, Elastic Cache, EBS & S3.
- Hands-on experience in versioning and CI/CD tools such as GitLab, AWS CodePipelines, etc.
- Good Understanding and Proficient in observability, monitoring and logging tools such as ELK Stack (Elasticsearch, Logstash, and Kibana), Prometheus, Nagios, Grafana, Cloudwatch or Datadog.
- Good experience in a scripting language like Bash, Ruby, Python or Go.
Extra awesome:
- Have experience with operating and tuning relational and NoSQL databases.
- Experience of working with cloud based machine learning platforms (AWS preferred).
