Site Reliability Engineer // AWS, DevOps, and AI/ML
Reston, VA
24 months
Local Resumes – mostly an In-person Interview
Description:
Overall years of experience:
8+ years of related experience in their specific area with experience leading teams on projects with similar scope and complexity.
Bachelor’s or master’s degree in computer science or equivalent.
Certifications: AWS Solutions Architect, Agile Certified Practitioner (ACP), or relevant cloud certifications.
Job Description:
We are seeking a highly skilled and experienced Site Reliability Engineer (SRE) to join our team. The ideal candidate will have a strong background in cloud platforms, DevOps practices, and modern software development frameworks. The SRE will play a critical role in designing, building, and maintaining highly scalable, fault-tolerant, and secure cloud infrastructure while ensuring operational excellence, high availability, and reliability.
Key Responsibilities:
Cloud Infrastructure & Automation:
Design, implement, and manage cloud-based infrastructure using platforms like AWS, Azure, or GCP.
Utilize Infrastructure-as-Code (IaC) tools such as Terraform, CloudFormation, and Ansible to automate deployments and configurations.
Create robust automation targeted at anomaly detection, toil reduction, recovery processes, and self-healing mechanisms, and optimize cloud costs.
DevSecOps & CI/CD:
Deep understanding of DevSecOps principles and CI/CD pipelines using tools like GitLab, Jenkins, SonarQube, Nexus/Artifactory, and Docker.
Implement security best practices, including IAM roles, RBAC, vulnerability remediation, and SAST/DAST/SCA tools.
Observability & Incident Management:
Design and implement monitoring, logging, and distributed tracing solutions using tools like AWS CloudWatch, Splunk/SignalFX, Dynatrace, and OpenTelemetry.
Lead root cause analysis, blameless postmortems, and proactive incident management to minimize MTTR and MTTD.
Define and monitor SLOs, SLIs, and error budgets to ensure system reliability.
Microservices & API Management:
Architect and manage microservices, serverless computing, and RESTful APIs.
Ensure fault tolerance and resilience using design patterns like Circuit Breaker, Retry, Timeout, and Bulkhead.
Chaos Engineering & Resiliency:
Conduct chaos engineering experiments using tools like AWS FIS and Chaos Toolkit.
Perform resiliency assessments using Resilience Hub and implement self-healing solutions.
Database & Application Support:
Manage and optimize database technologies such as PostgreSQL, MongoDB, DynamoDB, Oracle, and Redshift.
Provide production support, including incident response, problem management, and runbook creation. Participate in on-call rotations.
Collaboration & Communication:
Collaborate with cross-functional teams to implement shift-left testing practices (BDD, TDD, Unit, Regression).
Create and maintain architecture diagrams, knowledge articles, and disaster recovery plans.
Communicate effectively with stakeholders and demonstrate strong relationship management skills.
Required Skills & Qualifications:
Expertise in cloud platforms (AWS) and container orchestration.
Proficiency in programming/scripting languages such as Python, Java, Node.js, Bash, and PowerShell.
Strong knowledge of database technologies (e.g., PostgreSQL, MongoDB, DynamoDB, Oracle, Redshift).
Experience with DevOps tools (Jenkins, Docker, Nexus/Artifactory) and build tools (Maven, Gradle).
Familiarity with AI/ML integrations, event-driven architectures, and distributed systems.
Expertise in observability, logging, and monitoring tools (AWS CloudWatch, Splunk, Dynatrace, OpenTelemetry).
Strong understanding of security practices, including IAM, RBAC, and vulnerability management.
Experience with chaos engineering, resiliency assessments, and disaster recovery planning.
Proficiency in performance testing tools (JMeter, LoadRunner) and capacity planning.
Excellent verbal and written communication skills, with the ability to collaborate across teams.
Preferred Qualifications:
Experience with AI/ML libraries (e.g., NLTK, Transformers, Spacy, SciPy), Amazon SageMaker, and GenAI tools.
Familiarity with project management tools like JIRA, Confluence, and ServiceNow.
Knowledge of utilities like AWS CLI, POSTMAN, and curl.