Senior AI Operations Engineer

• Design, build, and maintain the centralised observability layer - instrumentation, dashboards, alerting rules, and telemetry pipelines using platforms such as Datadog, New Relic, Grafana, or Splunk

• Architect and implement AI-augmented operations tooling: conversational runbook interfaces, AI-driven incident analysis, and pattern recognition systems

• Lead complex incident response, perform root-cause analysis, and produce actionable post-mortems

• Contribute patches and instrumentation to product engineering codebases, ensuring they are architecturally sound and address root causes

• Contribute to vendor evaluation to assess and recommend appropriate technologies and automation tooling.

• Build and maintain the automation that powers the continuous improvement cycle: every incident results in a runbook, an automation, or a patch

• Own the technical execution of automation investments prioritised by frequency, resolution time, and blast radius

• Proactively identify and eliminate toil, maintaining the standard of no more than 50% of SRE time on reactive work

• Develop and maintain runbooks, ensuring they are accurate, current, and progressively automated

• Implement the Operational Readiness Gate - assess platforms against defined criteria before they transition from product engineering to operations ownership

• Shape platform operability during development - contributing instrumentation, health checks, and observability hooks before platforms enter BAU

• Provide technical input to platform architecture reviews from an operational perspective

• Mentor and coach L1 operators and junior L2 SREs, building their technical capability and engineering mindset

• Identify operators with engineering aptitude and support their development pathway from L1 to L2

• Contribute to the operations review by preparing flywheel metrics: L1 resolution rate, repeat incident rate, automation coverage, and toil budget compliance

• Foster a culture where SREs are engineers whose product is operational excellence

• Partner with product engineering teams on post-mortems, handover assessments, and operational obligation delivery

• Represent operational requirements in technical design discussions

• Communicate incident findings, operational risks, and improvement proposals clearly to the Operations Lead and wider team

• BSc/MSc degree in Computer Science or related quantitative or analytical field

• Significant hands-on experience as a Site Reliability Engineer or platform operations engineer at scale - you build and run systems, not just direct others

• Strong expertise in observability platforms (Datadog, New Relic, Grafana, Splunk, or equivalent) including dashboard design, alerting strategies, and telemetry pipeline implementation

• Strong working knowledge of OpenTelemetry, distributed tracing, and structured logging standards

• Proven track record of designing and implementing automation that materially reduces operational toil - strong scripting skills in Python and Bash, with the ability to build robust tooling beyond one-off scripts

• Experience assessing platform readiness and contributing to operational handover processes

• Strong hands-on skills with cloud infrastructure (Azure and/or AWS) including container orchestration, serverless architectures, and managed services

• Experience running or contributing significantly to post-mortem processes and translating findings into preventive engineering work

• Ability to implement precise technical solutions - you can instrument a system, configure meaningful alerts, and build automation that intervenes at the right point

• Experience mentoring junior engineers and contributing to team development

• Experience applying AI/ML to operational challenges - intelligent alerting, automated diagnosis, predictive incident detection, or conversational operations interfaces

• Familiarity with the AstraZeneca technology estate or regulated pharmaceutical environments

• Experience operating platforms that serve AI/ML workloads (LLM inference, model serving, data pipelines)

• ITIL, SRE, or operational excellence certifications or equivalent practical frameworks

• Experience working within multi-tier support structures with clear escalation paths

• Infrastructure-as-code expertise (Terraform, CloudFormation)

• Awareness to GxP and audit trail awareness.

• An engineering mindset applied to operations - you see every repeated manual task as an automation opportunity

• Comfort operating at the boundary between deep technical work and collaborative team contribution

• Creative, collaborative, and resilient

• Strong communicator who can explain technical complexity clearly to both engineers and leadership

• A bias toward systems thinking - you address root causes, not symptoms

• Self-directed with the ability to manage competing priorities across multiple platforms

When we put unexpected teams in the same room, we unleash bold thinking with the power to inspire life-changing medicines. In-person working gives us the platform we need to connect, work at pace and challenge perceptions. That's why we work, on average, a minimum of three days per week from the office. But that doesn't mean we're not flexible. We balance the expectation of being in the office while respecting individual flexibility. Join us in our unique and ambitious world.

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