Site Reliability Engineer
About The Position
At TWG Group Holdings, LLC (“TWG Global”), we drive innovation and business transformation across a range of industries—including financial services, insurance, technology, media, and sports—by leveraging data and AI as core assets. Our AI-first, cloud-native approach delivers real-time intelligence and interactive business applications, empowering informed decision-making for both customers and employees. We prioritize responsible data and AI practices to ensure ethical standards and regulatory compliance. Our decentralized structure enables each business unit to operate autonomously, supported by a central AI Solutions Group, while strategic partnerships with leading data and AI vendors fuel game-changing efforts in marketing, operations, and product development. You will collaborate with management to advance our data and analytics transformation, enhance productivity, and enable agile, data-driven decisions. By leveraging relationships with top tech startups and universities, you will help create competitive advantages and drive enterprise innovation. At TWG Global, your contributions will support our goal of sustained growth and superior returns, as we deliver rare value and impact across our businesses. We’re a fast-growing AI/ML team delivering high-impact use case solutions to financial institutions, insurers, and other regulated enterprises. Backed by proven leaders in finance and national security, our team is scaling rapidly to serve clients across North America with robust, secure, and production-grade AI solutions. Role Overview We are seeking a Site Reliability Engineer (SRE) to ensure the scalability, stability, and performance of our data platforms and ML infrastructure. You’ll work closely with data scientists, ML engineers, and platform vendors to deploy and monitor production systems, automate workflows, and reduce operational overhead.
Requirements
- 3–6 years of experience in DevOps, SRE, or backend engineering roles
- Proficient with tools like Docker, Kubernetes, Terraform, GitLab/GitHub Actions, Airflow
- Strong scripting in Python or Bash and familiarity with Linux environments
- Experience deploying and monitoring ML models or data pipelines in production
- Knowledge of observability stacks (e.g., Prometheus, Grafana, ELK, Datadog)
- Familiarity with cloud platforms (e.g., AWS, GCP, or Azure)
- Strong documentation, problem-solving, and incident response skills
Nice To Haves
- Experience supporting ML/AI workflows using Palantir Foundry.
- Exposure to compliance frameworks like SOC 2, ISO 27001, or financial regulations
- Knowledge of MLOps frameworks (e.g., MLflow, Kubeflow, SageMaker Pipelines)
- Ability to automate deployments, testing, and monitoring at scale
- Work on real-world AI applications with high-impact clients
- Collaborate with world-class data scientists, engineers, and product leaders
- Flat org structure, high trust, high autonomy
- Competitive salary + performance-based incentives
Responsibilities
- Build and maintain infrastructure to support real-time and batch ML workloads
- Implement observability tools (logging, monitoring, alerting) for model performance and system uptime
- Design and manage CI/CD pipelines for ML and data applications
- Ensure high availability, disaster recovery, and rollback capabilities for production environments
- Manage access controls, secrets, and security policies in collaboration with compliance and IT
- Troubleshoot incidents, lead postmortems, and drive root-cause resolution
- Work with U.S. and international teams to provide 24/7 coverage across time zones
Benefits
- Competitive salary + performance-based incentives
- full range of medical, financial, and/or other benefits
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
