Senior MLOps Engineer

*What do we do? *

We build a Cloud Platform that integrates Services and Applications.
We develop and support the platform that processes billions of events a day, works with over 300 different applications, and is trusted by over 2000 companies including leading brands like Slack, Splunk, Visa, Salesforce, Panera Bread, etc.

We are Leaders in iPaaS solutions in the US market, rapidly launching in the EU & APAC.
Our investors include Storm Ventures and top 2 SaaS companies on the market - Salesforce Ventures and Workday Ventures.

6 000 + customers
1 000 + Connectors to Apps, Database, files, APIs (Cloud, On-Premise)

What does our ML/AI team do?
The team supported Generative AI solution for automation and integration https://www.workato.com/genie

Our Team
International Sr-level professionals from all over the Globe, experienced in building high-performing, scalable, enterprise-grade applications.
Unique team of multinational professionals with integration, cloud, consumer experience

As a Senior Infrastructure Engineer, you will be responsible for deploying, scaling, and maintenance of services at the ML/AI team. You will closely work with ML Engineers and DataScientists as a part of a small, flexible team and will have a direct impact on the process of modernization and maturation of the platform including infrastructure architecture decisions.

Responsibilities:
We are currently seeking a seasoned Senior Infrastructure Engineer with experience in AI domain.

Requirements:

• 7+ years professional experience in hands-on engineering roles (DevOps/SRE), BS or MS in the CS field (or equivalent experience).
• 1+ year of experience with hosting AI models (ML flow, AWS sagemaker, Azure AI, kubernetes)
• 1+ year of experience with ML Ops (ML flow, vector databases (qdrant), dagster)
• Kubernetes Expertise: Strong experience managing Kubernetes clusters and workloads, specifically using EKS (Elastic Kubernetes Service).
• Programming Skills: Proficiency in Python language is essential. Ability to program in other languages such as Go, Ruby, or JavaScript is a plus.
• CI/CD Tools: Experience creating scalable development and integration pipelines using CI/CD tools such as GitHub Actions, Argo Workflows, GitLab CI, or similar solutions.
• Kubernetes Deployments: Expertise in deploying Kubernetes-based services using tools like Kustomize, Helm, ArgoCD, or similar, following a GitOps approach.
• Cloud Architectures: Hands-on experience with cloud-based architectures, particularly Amazon Web Services (AWS).
• Networking and Web Services: Strong understanding of networking fundamentals and web services architecture.
• Infrastructure as Code: Experience managing complex infrastructure, including Kubernetes clusters, VPC networking, and security policies, using Infrastructure as Code tools like Terraform.
• Containerization: Hands-on experience with containers, including creating and optimizing Dockerfiles, using docker-compose, and a deep understanding of related technologies (kernel features, container networking, image structure, and registry).
• Software Packaging and Testing: Familiarity with software packaging tools, functional testing, security validation tools and services, and code coverage tools.
• Compliance and Security: Operating Kubernetes clusters in compliance-regulated environments and understanding kernel-level container technologies such as seccomp, namespaces, and cgroups.
• Security Regulations and Compliance: Experience with cloud and infrastructure security regulations and compliance programs, including SOC2, ISO27001, HIPAA, GDPR, and CCPA.