Junior SRE Engineer Guadalajara Mexico

Role Overview At Rehire, we are partnering with a US-based data engineering and cloud technologies company to find a Junior SRE Engineer to join its Reliability Engineering team. You will be embedded with the SRE function of a financial services client, supporting a regulated consumer-lending platform on AWS with hundreds of microservices and event-driven pipelines, where reliability directly impacts customer trust and compliance. This is a unique opportunity to grow in an environment where AI is already part of day-to-day operations, including an AI SRE co-pilot, purpose-built AI agents for incident triage and monitoring, and a formal AI governance program. Working under the guidance of senior engineers and architects, you will help operate, improve, and learn from this AI-driven reliability program. Key Responsibilities: · Support incident response as a shadow or secondary responder, using AI-driven detection, correlation, and root-cause analysis tools. · Help build incident timelines from metrics, logs, traces, and deploy history, and document postmortems and corrective actions through to closure. · Help operate and monitor AI SRE sub-agents (incident summarization, monitor-gap detection, usage attribution), flagging anomalies for senior review. · Build and maintain Datadog monitors, dashboards, and SLO definitions as code using Terraform, and support SLI/SLO and error-budget reviews for critical customer journeys. · Help reduce alert noise with AI/ML-assisted detection (anomaly, outlier, and forecast monitors, dynamic thresholds) and run recurring monitor-hygiene reviews. · Support the day-to-day reliability of AWS workloads (ECS/Fargate, EKS, Lambda, RDS/Aurora, ALB, SQS/SNS, Step Functions). · Identify capacity, saturation, and cloud cost anomalies, and help attribute spend and telemetry volume to owning teams and services. · Write automation in Python and Bash against platform APIs (Datadog, AWS, GitHub, PagerDuty, Jira) and contribute Terraform modules through pull requests. · Help integrate reliability controls and AI-assisted checks into CI/CD pipelines, and create runbooks progressively automated toward self-healing. · Participate in architecture, reliability, and AI-risk reviews, learning how compliance frameworks (PCI-DSS, SOC 2, SOX, GLBA) apply in a regulated environment. Requirements: · Bachelor's degree in Computer Science, Engineering, or a related field. · 1–3 years of experience in SRE, DevOps, cloud infrastructure, platform, or production-support engineering. · Advanced English (oral and written). REQUIRED · Hands-on exposure to AWS (or an equivalent hyperscaler) across compute, networking, storage, and managed database services. · Exposure to at least one observability platform ( Datadog preferred ; Grafana/Prometheus, New Relic, CloudWatch, or ELK/OpenSearch also relevant). · Foundational understanding of SLI, SLO, and error-budget concepts. · Foundational knowledge of containers and orchestration (Docker, ECS, or Kubernetes) and serverless execution models. · Beginner-to-intermediate experience with Infrastructure as Code ( Terraform preferred ; Ansible or CloudFormation acceptable). · Scripting experience in Python, Bash, or similar, including consuming REST APIs and parsing JSON. · Basic Linux troubleshooting and networking fundamentals (DNS, TLS, load balancing, timeouts, and retries). · Comfort with Git, pull-request workflows, and CI/CD tools (GitHub Actions, Jenkins, GitLab CI, ArgoCD, or similar). · Familiarity with incident management and on-call concepts (severity models, escalation policies, PagerDuty or Opsgenie). · Experience in product engineering services, enterprise software, or fintech is a plus. · Awareness of compliance frameworks (PCI-DSS, SOC 2, SOX, GLBA) is a plus. Key Competencies: · Automation mindset: you would rather automate a task the second time you do it than the tenth. · Good judgment to escalate early instead of sitting on an uncertain production signal. · Clear written communication: you can explain an incident, a metric, or a trade-off to someone who was not in the room. · Curiosity about LLM-based assistants and agents applied to operations, and about how to verify that their output is correct. Preferred Certifications (not required): · AWS Certified Cloud Practitioner or an Associate-level AWS certification. · HashiCorp Certified: Terraform Associate. · Datadog Fundamentals or an equivalent observability certification. · Certified Kubernetes Administrator (CKA) or KCNA. About the Position: · Work Schedule: US shift presential at Guadalajara, Mexico. · Work Modality: Full-time contractor basis. · Competitive Salary Paid in USD. · Work Environment: Dynamic and collaborative. · Professional Growth: Hands-on learning in AI-driven SRE practices and opportunities for career advancement. If you meet the requirements and are interested in this exciting opportunity, apply at www.rehire.ar/jobs and send us your CV!