Role Overview
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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

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- 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

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- 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, NewRelic, 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

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- Automation mindset: you would rather automate a task the second time you do it than the tenth.

- Good judgment to escalat e 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)

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- 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

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- Work Schedule: US shift presential at Guadalajara, Mexico.

- Work Modality: Full-time contractor basis.

- Competitive Salary Paid in USD.

- Work Environment: Dynamic and collaborative. xhfqzwm

- Professional Growth: Hands-on learning in AI-driven SRE practices and opportunities for career advancement.

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📌 Junior Sre Engineer Guadalajara Mexico (Albacete)
🏢 ReHire
📍 Albacete