AstraZeneca is a integral, innovation-driven BioPharmaceutical business that focuses on the discovery, development and commercialisation of prescription medicines for some of the world's most serious diseases. But we're more than one of the world's leading pharmaceutical companies.
Where you are empowered to push the boundaries of science and unleash your entrepreneurial spirit. There's no better place to make a difference to medicine, patients and society. Always committed to lifelong learning, growth and development.
ABOUT OUR ENTERPRISE AI PLATFORMS & SERVICES TEAM
Play an increasingly crucial role in driving disruptive transformation on our journey to becoming a digital and data-led enterprise. Unleash the power of our latest innovations in data, machine learning and technology to turn complex information into life-changing and practical insights. Work in synergy with leading experts in our specialist communities. We are looking for a Senior AI Operations Engineer to be a hands‐on technical leader within our AI/ML platform operations function. Reporting to the AI for Operations Lead, you will be the primary executor and technical driver across our growing platform estate, built on Azure and AWS. The ideal candidate will have deep, current experience in site reliability engineering and will combine strong individual contribution with mentoring and technical leadership of L1 and L2 engineers.
You will operate within a three-tier operations structure (L1 Runbook Operators, L2 Site Reliability Engineers, L3 Product Engineering interface) and be the senior hands‐on practitioner who builds the automation, designs the observability, and drives the continuous improvement flywheel day‐to‐day.



You will be a key contributor to AI‐augmented operations — building and refining AI‐powered tools for runbook querying, incident pattern analysis, and automated diagnosis.
This is a senior technical position for someone who sees operations as an engineering discipline and who can design, build, and instrument systems to the highest standard while coaching others to do the same.
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
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
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
L1 resolution rate,



repeat incident rate, automation coverage, and toil budget compliance
Partner with product engineering teams on post‐mortems, handover assessments, and operational obligation delivery
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
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
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
Experience mentoring junior engineers and contributing to team development
Experience operating platforms that serve AI/ML workloads (LLM inference, model serving, data pipelines)
ITIL, SRE, or operational excellence certifications or equivalent practical frameworks
Infrastructure-as-code expertise (Terraform, CloudFormation)
Personal Qualities
An engineering mindset applied to operations — you see every repeated manual task as an automation opportunity
That's why we work, on average, a minimum of three days per week from the office. We balance the expectation of being in the office while respecting individual flexibility. We welcome and consider applica

📌 Senior AI Operations Engineer (Ciudad de México)
🏢 Astrazeneca
📍 Ciudad de México