Job responsibilities
- Advocate and embody site reliability principles, fostering a culture of excellence and technical influence within your team.
- Leverage AI tools to enhance operational effectiveness and automate processes, ensuring high-quality customer service.
- Spearhead projects aimed at enhancing the reliability and stability of applications and platforms.
- Utilize data-driven analytics and AI technologies to automate detection, diagnosis, resolution processes, elevate service levels and drive continuous improvement.
- Engage stakeholders to establish realistic service level objectives and error budgets, ensuring alignment with customer expectations.
- Exhibit advanced technical proficiency in one or more domains, proactively addressing technology-related bottlenecks.
- Employ AI-driven solutions to streamline processes and enhance operational efficiency.
- Serve as the primary contact during major incidents, demonstrating the ability to swiftly identify and resolve issues to prevent financial losses.
- Act as a culture carrier by documenting and disseminating knowledge through internal forums and communities of practice.
- Mentor team members, guiding them in the strategic adoption of AI technologies to enhance operational effectiveness and customer service.
Required qualifications, capabilities, and skills
- Formal training or certification on site reliability engineering concepts and 5+ years applied experience.
- Proven success in an SRE or senior DevOps role, with deep knowledge of service level indicators/objectives (SLIs/SLOs), incident management, postmortem analysis, and systems reliability.
- Expert with observability stacks (e.g. Datadog/Dynatrace, Prometheus, Grafana, Splunk, OpenTelemetry), including deep experience correlating telemetry across services and time.
- Hands-on skills in coding (at least one high-level programming language), cloud platforms (AWS or GCP), container orchestration (Kubernetes), infrastructure as code (Terraform), and resilient CI/CD pipelines.
- Active experience or deep curiosity in applying AI to operations—such as LLM-based copilots, anomaly detection, automated runbooks, autonomous agents.
- A track record of delivering under pressure. You finish what you start, adapt to uncertainty, and thrive in high-accountability environments.
- You deconstruct complexity, organize effectively, and drive clarity into ambiguous operational environments. Documentation and design are second nature.
- Outstanding communication, empathy, and professionalism—especially during incidents. You recognize that great systems serve real people.
Preferred qualifications, capabilities, and skills
- Experience with operational and compliance rigor in banking, fintech, or similar.
- Manage and optimize various types of databases, including relational, NoSQL databases.
- Experience with game days, chaos experiments, or failure-mode analysis to improve service robustness.
- A background in mentoring engineers or leading technical knowledge-sharing, especially around AI and SRE best practices.
- Ability to initiate and implement ideas to solve business problems
- Strong communicator with excellent problem-solving, critical thinking, and analytical reasoning skills, along with attention to detail and a passion for innovation.