What are the responsibilities and job description for the Senior Site Reliability Engineer position at Elsevier?
Senior Site Reliability Engineer
About the team:
Embedded Innovation Teams are cross-functional squads embedded within our segments to rapidly turn internal AI experimentation into validated, reusable solutions, building the capabilities we need to deliver customer value and growth. We work problem-first rather than tool-first, directly inside segment and function teams, improving the internal workflows that help our people deliver better outcomes for customers, faster.
About the role:
As a Senior Site Reliability Engineer (SRE), you will play a key role in ensuring the reliability, scalability, and performance of our critical platforms and services. You will lead complex reliability initiatives, drive automation efforts to reduce operational toil, and help build resilient systems that deliver exceptional customer experiences.
You will leverage your expertise in observability, incident response, and distributed systems to proactively identify and resolve reliability challenges. Working closely with engineering teams, you will design and implement solutions that improve service availability, streamline operations, and enhance system recovery capabilities.
You will hold a high bar on code quality, flag risks and blockers early, and work alongside host-function stakeholders to make sure what you build fits real workflows, not assumed ones. You will also support handover and capability-building so the solution is owned and operable after the squad moves on.
Key Responsibilities:
- Creating monitoring queries and establishes service level baselines.
- Supporting senior engineers during incidents.
- Making contributions during post-mortems and RCAs.
- Participating in disaster recovery tests.
- Implementing automation and executes code in production environments.
- Contributing to SRE knowledge documentation.
- Supporting the deployment, monitoring, and reliability of services integrating AI tools.
- Supporting architecture and senior engineers in the creation of infrastructure topology drawings and deployment workflows.
- Carrying out the testing of availability, reliability, and recoverability in non-production environments.
Requirements:
- Advanced Terraform: Expertise in modules, providers, state management, lifecycle controls, drift detection, safe refactoring, and remote state (S3, locking, cross-stack dependencies).
- AWS Operations: Hands-on experience managing production, multi-account, multi-region AWS environments across ECS, RDS, ALB, VPC, IAM, Route53, ECR, S3, Lambda, DynamoDB, SQS, Secrets Manager, KMS, and CloudWatch.
- GitHub Actions CI/CD: Experience building and troubleshooting reusable workflows, OIDC authentication, approval gates, runners, Terraform deployments, application deployments, and migration pipelines.
- ECS Fargate & Containers: Knowledge of Docker, ECR, ECS task definitions/services, IAM roles, health checks, autoscaling, ALB integration, and deployment rollbacks.
- AWS Networking & Security: Proficiency in VPCs, networking, ALBs, Route53, ACM/TLS, IAM, OIDC, Secrets Manager, KMS, and cloud security best practices.
- Incident Response & Observability: Skilled in troubleshooting using logs, metrics, alarms, deployment history, root cause analysis, rollback decisions, and operational runbooks.
- Linux & Automation: Strong Linux and Git fundamentals with Bash/Python scripting for AWS CLI automation, CI/CD, and operational tooling.
- AI Tooling Deployment: Hands-on experience integrating and operating AI services and APIs in production, including monitoring, reliability, and security practices for AI-powered features.
- Developer Enablement: Ability to support multiple engineering teams, troubleshoot across infrastructure and application layers, document solutions, and enable secure self-service practices.