Cloud SRE & DevOps Engineer

Company Overview Soros Fund Management LLC (SFM) is a global asset manager and family office founded by George Soros in 1970. With $28 billion in assets under management (AUM), SFM serves as the principal asset manager for the Open Society Foundations, one of the world’s largest charitable foundations dedicated to advancing justice, human rights, and democracy. Distinct from other investment platforms, SFM thrives on agility, acting decisively when conviction is high and exercising patience when it’s not. With permanent capital, a select group of major clients, and an unconstrained mandate, we invest opportunistically with a long-term view in a wide range of strategies and asset classes, including public and private equity and credit, fixed income, foreign exchange, and alternative assets. Our teams operate with autonomy, while cross-team collaboration strengthens our conviction and empowers us to capitalize on market dislocations. At SFM, we foster an ownership mindset, encouraging professionals to challenge the status quo, innovate, and take initiative. We prioritize development, enabling team members to push beyond their roles, voice bold ideas, and contribute to our long-term success. This culture of continuous growth and constructive debate fuels innovation and drives efficiencies. Our impact is measured by both the returns we generate and the values we uphold, from environmental stewardship to social responsibility. Operating as a unified team across geographies and mandates, we remain committed to our mission, ensuring a meaningful, lasting impact. Headquartered in New York City with offices in Greenwich, Garden City, London, and Dublin, SFM employs 200 professionals. Team Overview: Reports To: Head of Cloud SRE & DevOps Engineering Other Key Relationships: Cybersecurity analysts, Software Development engineers   Job Overview: We are seeking a mid-to-senior level engineer to join our Cloud SRE & DevOps Engineering team in London, focused on building, operating, and evolving the cloud infrastructure and delivery platforms that support our trading and investment systems. This role sits at the intersection of Cloud Engineering, SRE, DevOps, Platform Engineering, and Production Engineering, and is designed for individuals who take ownership of systems running in production. You will be responsible for designing and operating resilient, scalable environments across AWS and Kubernetes, while enabling engineering teams through modern DevOps and GitOps practices. The position reflects a strong Site Reliability Engineering (SRE) mentality, with emphasis on reliability, observability, automation, and operational excellence. You will play a key role in advancing the firm’s cloud transformation strategy, ensuring systems are built for performance, stability, and scale. This is a hands-on role requiring deep technical expertise, accountability for production systems, and a mindset oriented toward continuous improvement, risk management, and engineering efficiency. The role also contributes to evolving platform capabilities supporting AI and data-driven workloads. You will work closely with software engineering, cybersecurity, and data teams to deliver secure, scalable, and high-performing systems, while improving developer experience and platform maturity across the organization. Major Responsibilities: Cloud Infrastructure & Kubernetes Design, build, and operate scalable AWS-based infrastructure supporting trading systems Work across hybrid or multi-cloud environments (AWS and Azure) Manage and optimize Kubernetes environments (EKS), ensuring resilience, scalability, and performance Utilize Kubernetes ecosystem tooling (e.g., Helm) to support application deployment and lifecycle management Develop reusable infrastructure using Terraform and infrastructure as code principles   Database Cloud Management & Administration Manage the automated delivery of Snowflake configurations through CICD pipelines Help administration of Microsft SQLServer, Snowflake and AWS Aurora   CI/CD & DevOps Practices Design and maintain CI/CD pipelines using tools such as GitHub Actions Promote Git-based workflows and support GitOps practices (e.g., ArgoCD) Improve deployment reliability, consistency, and engineering velocity Production Engineering & Reliability Own and operate business-critical production systems with a strong focus on uptime, performance, and risk mitigation Troubleshoot and resolve complex issues across distributed systems, cloud infrastructure, and Kubernetes environments Implement and enhance monitoring, logging, and alerting using tools such as Datadog, AWS CloudWatch, Geneos, and LogicMonitor Apply cloud security best practices, including IAM, secrets management, and vulnerability scanning Support and optimize relational database systems (e.g., PostgreSQL, MySQL, SQL Server, Aurora), ensuring performance and high availability Contribute to backup, recovery, and resilience strategies across infrastructure and data layers Drive improvements aligned with SRE principles, including reliability, observability, and operational maturity Developer Enablement Improve developer experience through automation, standardization, and self-service capabilities Partner with engineering teams to streamline development and deployment workflows AI & Emerging Workloads Support infrastructure for AI/ML and data-driven workloads, including scalable compute and data processing patterns Enable deployment patterns for modern, data-intensive applications Evaluate emerging technologies relevant to AI-enabled platforms What We’re Looking For: Core Technical Expertise Strong hands-on experience with AWS in production environments Experience working in hybrid or multi-cloud environments (AWS and Azure) Deep experience with Kubernetes and containerized systems (Docker, EKS) Strong familiarity with Kubernetes tooling, including Helm Proven experience with infrastructure as code (Terraform preferred) Strong experience building and managing CI/CD pipelines (GitHub Actions or similar) Proficiency in Python, Shell, or PowerShell for automation   Production & Systems Engineering Strong understanding of distributed systems, networking, and cloud architecture Experience operating and supporting production systems with high availability and performance requirements Experience diagnosing and resolving complex production incidents in distributed environments Experience supporting relational databases (e.g., PostgreSQL, MySQL, SQL Server, Aurora) in cloud environments Monitoring & Observability Hands-on experience with observability tools such as Datadog, AWS CloudWatch, Geneos, or LogicMonitor (or comparable enterprise monitoring platforms), including designing metrics, alerts, and dashboards for production systems   DevOps & Engineering Practices Strong grounding in DevOps methodologies, including automation, continuous delivery, and infrastructure standardization Experience working with Git-based workflows and modern software engineering practices Ability to balance speed, stability, and risk in production environments   Professional Attributes Strong analytical and troubleshooting skills Ability to operate effectively in high-performance, time-sensitive environments Clear communication across technical and non-technical stakeholders Ownership mindset with accountability for critical systems   Nice to Have: AI & Data Experience supporting AI/ML workloads or data platforms Familiarity with LLM APIs, vector databases, or GPU-based environments Exposure to modern data platforms such as Databricks, Google BigQuery, or Amazon Redshift   Financial Services Experience supporting trading or investment systems Understanding of trading workflows (OMS, order entry, trade booking), market data, or FIX protocol What We Value: Bachelor's degree in Engineering, Computer Science, Information Systems, or equivalent experience. Hands-on experience with cloud platforms such as AWS, Azure, and Snowflake, with a solid understanding of IaaS, PaaS, and SaaS in hybrid environments. Experience in cloud infrastructure or server-side development, with a fundamental understanding of containerization and Kubernetes. Proficiency in programming languages like PowerShell and Python, with experience in DevOps tools such as Terraform, Docker, and Kubernetes. Deep understanding of CI/CD tools (e.g., Octopus, Bamboo, Azure DevOps, Git Actions) and configuration management. Expertise in automation scripting, infrastructure as code (IaC), and immutable infrastructure using tools like AWS CloudFormation or Terraform. Familiarity with observability frameworks (DataDog, OpenSearch, and LogicMonitor). Familiarity with networking, storage, and database concepts. Ability to craft clear, effective communications for both technical and non-technical audiences. Strong analytical and troubleshooting skills, attention to detail, ability to multitask, and work effectively in a fast-paced environment. Proficiency in writing scripts using Python, PowerShell, Bash, and experience with technologies like Docker, Lambda functions, and Kubernetes. Hands-on experience with Terraform, Packer, Git, and Jira is considered a plus. Integration with JIRA and GitHub is a plus Experience in designing, developing, and implementing ETL/ELT processes using Snowflake and related technologies.   In addition to a base salary, the successful candidate will also be eligible to receive a discretionary year-end bonus.        In all respects, candidates need to reflect the following SFM core values:   Integrity   //   Teamwork   //   Smart risk-taking   //   Owner’s Mindset   //   Humility      Discover how SFM continues to drive impactful investments and supports the global mission of the Open Society Foundations.                 Offices: London, England, United Kingdom (SFM-UK);