• Guides and assists others in the areas of building appropriate level designs and gaining consensus from peers where appropriate, supporting adoption of site reliability engineering best practices within your team
• Collaborates with other software engineers and teams to design, develop, test, and implement deployment and reliability approaches using automated continuous integration and continuous delivery pipelines
• Uses enterprise-authorized AI capabilities within the work environment to accelerate incident triage, troubleshooting, and post-incident analysis, validating outputs and handling operational data according to sensitivity and security requirements.
• Continuously monitor operational signals (alerts, dashboards, service health indicators, and desk/user feedback) and drive rapid engagement, ownership, and coordination when issues emerge.
• Enhance production observability and reliability by improving instrumentation, dashboards, and alert quality; use trend and incident data to reduce noise, prevent recurrence, and measurably lower MTTR and incident frequency.
• Own and improve the support operating model: maintain/run runbooks, ensure clean handoffs and escalation paths, manage shift coverage, and drive disciplined post-incident follow-through (actions, owners, due dates).
• Partner with engineering and adjacent service owners to drive root-cause fixes and stronger change/release standards, identify cross-service dependencies early, and build lightweight automation/self-service tooling to reduce manual steps and speed repeatable triage.
• Lead L1/L2 production support using SRE practices: quickly triage incidents, investigate likely causes, apply safe mitigations/workarounds, and provide timely, clear stakeholder updates through to resolution.

• Applies enterprise-authorized AI capabilities within the work environment to identify patterns in operational signals that indicate reliability risk or recurring toil, prioritizing reuse-first improvements tied to SLO outcomes.

Required qualifications, capabilities, and skills

• Formal training or certification on site reliability engineering concepts and 3+ years applied experience 
• Proficient in site reliability culture and principles and familiarity with how to implement site reliability within an application or platform
• Proficient in at least one programming language such as Python, Java/Spring Boot, and .Net
• Working knowledge of using enterprise-authorized AI capabilities within the work environment to support SRE workflows with strong validation habits and awareness of data sensitivity
• Ability to validate AI-assisted operational recommendations before applying changes, escalating when uncertain and following data sensitivity requirements
• Proficient knowledge of software applications and technical processes within a given technical discipline (e.g., Cloud, AI, Android, etc.)
• Practical cloud experience in AWS supporting production services (visibility/troubleshooting, deployments, and operational hygiene)
• Ability to write code to automate support work (e.g., Python, Java, or similar) and reduce operational toil
• Experience operating in time-sensitive environments (market hours or similar), with strong incident discipline and stakeholder communication
• Strong debugging fundamentals across distributed systems (logs/metrics, latency analysis, dependency failures, data issues)

Preferred qualifications, capabilities, and skills

• Prior Markets experience, especially pricing / risk / market data support (Fixed Income a plus)
• Experience with Datadog (metrics/logs/traces), alert tuning, dashboards, and basic SLO concepts
• Familiarity with messaging/streaming patterns (Kafka/MQ) and data quality checks in execution and pricing pipelines
• Experience applying AI-assisted tooling to reduce support toil