Requirements:
Your Experience
​4+ years of experience as a DevOps engineer or Site Reliability Engineer.
Deep knowledge and experience in cloud infrastructure such as AWS, Azure, or Google Cloud.
Strong hands-on experience operating production workloads on AWS, with an emphasis on serverless systems (Lambda, DynamoDB, OpenSearch, S3, API Gateway, EventBridge, SQS/SNS, CloudFront, IAM, and CloudWatch).
Experience with Infrastructure as Code (IaC) tools such as Terraform, AWS CDK, or CloudFormation.
Experience with containerization and orchestration technologies like Docker, Kubernetes, or ECS/ECR.
Experience with CI/CD tools and configuration management systems like Jenkins, Git, or Ansible.
Practical experience with high-availability design, disaster recovery planning, backups, restores, and rollbacks across multiple AWS regions.
Proficiency in scripting with Bash and Python.
Experience with end-to-end system ownership, including on-call participation, incident response, and root-cause analysis.
Fluent in English with strong writing skills
Preferred Qualifications
Hands-on experience with monitoring and alerting tools like Datadog, CloudWatch, or PagerDuty.
Good understanding of cloud networking and topology.
Experience mentoring other engineers and setting technical standards.
Proven ability to reduce manual operational work through automation and tooling.
Strong ability for rapid self-learning and adoption of new technologies.

Requirements:
4+ years of experience as a DevOps engineer
Deep knowledge and experience in cloud infrastructure such as AWS, Azure, or Google Cloud
Experience with Infrastructure as Code (IaC) tools (e.g.Terraform, AWS CDK, CloudFormation)
Experience with Containers and Orchestrators (Docker, Kubernetes, ECS, etc.)
Experience with CI/CD Tools and Configuration Management Systems (e.g. Jenkins, Git, Ansible, Terraform, etc.)
Experience with any of the Observability and Logging tools preferably DataDog
Good understanding and ability to manage and append Networking on cloud and cloud topology
Good script skills - Bash and Python
Decision-making skills: taking into account both architectural and business considerations, at times with incomplete information.
Proactive by nature; internal drive for excellence and improvement
Strong ability to use new technologies and understand them in depth through rapid self-learning
Fluent in English, good writing skills
Additional Information
Experience in testing methodologies and developing tests (e.g Unit tests, integration tests, system tests)
Strong networking foundations (TCP/IP, DNS, Network Protocols, Routing)
Security principles and techniques (Risk management, Threat modeling, secure configuration)
Database usage experience and understanding
Experience with Agile development and practices
Cloud Solution Architect Certificate.

Requirements:
4+ years of experience as a DevOps engineer
Deep knowledge and experience in cloud infrastructure such as AWS, Azure, or Google Cloud
Experience with Infrastructure as Code (IaC) tools (e.g.Terraform, AWS CDK, CloudFormation)
Experience with Containers and Orchestrators (Docker, Kubernetes, ECS, etc.)
Experience with CI/CD Tools and Configuration Management Systems (e.g. Jenkins, Git, Ansible, Terraform, etc.)
Experience with any of the Observability and Logging tools preferably DataDog
Good understanding and ability to manage and append Networking on cloud and cloud topology
Good script skills - Bash and Python
Decision-making skills: taking into account both architectural and business considerations, at times with incomplete information.
Proactive by nature; internal drive for excellence and improvement
Strong ability to use new technologies and understand them in depth through rapid self-learning
Fluent in English, good writing skills
Additional Information
Experience in testing methodologies and developing tests (e.g Unit tests, integration tests, system tests)
Strong networking foundations (TCP/IP, DNS, Network Protocols, Routing)
Security principles and techniques (Risk management, Threat modeling, secure configuration)
Database usage experience and understanding
Experience with Agile development and practices
Cloud Solution Architect Certificate.

Requirements:
Your Expereience:
6+ years of Devops engineering experience on mission-critical, enterprise-level systems in a hybrid (both cloud and on-prem) environment.
3+ years of hands-on experience with cloud environments, preferably Google Cloud Platform (GCP).
Expertise in configuration management and Infrastructure-as-Code using frameworks such as Terraform and Ansible.
Strong programming/scripting knowledge in languages like Python, Bash, or Go for infrastructure automation.
Demonstrated experience with CI/CD pipelines (e.g., GitHub, Jenkins, Artifactory) and a strong foundation in Linux/Unix administration.
Bachelor's degree in Computer Science, Information Technology, or a related field, or equivalent practical experience.
Preferred Qualifications
Experience with containerization and orchestration technologies, particularly Kubernetes.
Hands-on experience with monitoring and observability tools such as Datadog, Grafana, or Prometheus.
Understanding of networking principles including firewalls, load balancers, and complex network designs.
A curious and positive mindset with a passion for applied learning and challenging existing processes for continuous improvement.

Requirements:
5+ years of experience as a DevOps Engineer or similar
infrastructure-focused role.
Hands-on experience with Azure, Aws, or GCP.
Experience with CI/CD tools such as Jenkins, GitHub Actions, or similar platforms.
Strong knowledge of Terraform and Infrastructure as Code practices.
Experience with Docker, Kubernetes, Argo CD, and Kustomize.
Experience designing and operating production-grade Kubernetes saas platforms or enterprise environments.
Experience with monitoring and observability tools such as Prometheus, Grafana, and ELK.
Strong troubleshooting, analytical, and communication skills.
B.Sc. in Computer Science, Computer Engineering, Information Systems, or a related field (or equivalent practical experience).
Nice to have:
Experience supporting AI, Machine Learning, or Generative AI workloads, including familiarity with MLOps concepts, AI deployment platforms, or cloud-based AI services.

Requirements:
Your Expereience:
6+ years of Devops engineering experience on mission-critical, enterprise-level systems in a hybrid (both cloud and on-prem) environment.
3+ years of hands-on experience with cloud environments, preferably Google Cloud Platform (GCP).
Expertise in configuration management and Infrastructure-as-Code using frameworks such as Terraform and Ansible.
Strong programming/scripting knowledge in languages like Python, Bash, or Go for infrastructure automation.
Demonstrated experience with CI/CD pipelines (e.g., GitHub, Jenkins, Artifactory) and a strong foundation in Linux/Unix administration.
Bachelor's degree in Computer Science, Information Technology, or a related field, or equivalent practical experience.
Preferred Qualifications
Experience with containerization and orchestration technologies, particularly Kubernetes.
Hands-on experience with monitoring and observability tools such as Datadog, Grafana, or Prometheus.
Understanding of networking principles including firewalls, load balancers, and complex network designs.
A curious and positive mindset with a passion for applied learning and challenging existing processes for continuous improvement.

Requirements:
Your Experience:
4+ years operating production infrastructure in AWS.
Deep hands-on experience with Kubernetes, Helm, ArgoCD, Terraform, and CI/CD.
Strong experience with observability and alerting in Datadog or comparable platforms.
Solid grounding in Linux, networking, cloud security, and reliability best practices.
Strong scripting skills in Python and Bash.
Proven ability to own platform projects end-to-end, from design through production operation and ongoing improvement.
Strong troubleshooting across distributed systems, Kubernetes, CI/CD, and live incidents.
Collaborative mindset - comfortable working across engineering, security, product, and leadership.
Comfort in a fast-paced, high-ownership environment where priorities shift but production quality doesn't.
Genuine interest in applying AI, automation, and intelligent workflows to operational work.
Key qualities
Ownership-driven - You take responsibility for the systems you build and operate, from design through production support and continuous improvement.
Collaboration - You work effectively across engineering, security, product, and leadership to align priorities and drive shared outcomes.
Developer experience focus - You are committed to reducing friction for engineering teams through thoughtful automation, self-service workflows, and reliable internal tooling.
Innovation balanced with pragmatism - You actively explore new approaches, particularly in AI-assisted operations, while weighing them against reliability, maintainability, and operational simplicity.
Security mindset - You design and build with least privilege, auditability, and production safety as foundational principles rather than afterthoughts.
Clear communication - You articulate infrastructure, reliability, cost, and security tradeoffs precisely to both technical and non-technical stakeholders.

Requirements:
At least 6 years of experience as a DevOps/SRE engineer in a cloud environment
Hands-on, production-level AWS experience.
Hands-on production experience with Kubernetes and containerization
Experience with Terraform/Terragrunt (or similar Infrastructure-as-Code tools) - required
Strong Bash scripting skills
Deep understanding of SRE principles: SLOs, SLIs, error budgets, toil reduction, blameless post-mortems
Strong incident management / on-call experience
Solid understanding of APIs, microservices, and distributed systems
Demonstrated experience leading a project end-to-end, from defining success criteria through delivery and measurement
Communicates effectively across teams and can drive long-term technical planning
Practical experience with AI-assisted engineering tools (e.g., Claude, Cursor) and MCP-style integrations is a strong plus
Experience building AI/ML infrastructure (model deployment, inference pipelines)-plus.

Requirements:
What you have:
3-5 years of hands-on experience in DevOps, Platform Engineering, or Infrastructure Engineering roles.
Strong hands-on experience working with AWS in production environments.
Proven experience with AWS services such as EKS, EC2, IAM, VPC, Route 53, S3, RDS, Lambda, CloudWatch, or similar services.
Strong experience with Kubernetes and containerized environments.
Hands-on experience with Infrastructure as Code tools, preferably Terraform.
Experience building and maintaining CI/CD pipelines using GitHub Actions, GitLab CI, Argo CD, or similar technologies.
Experience writing automation or production-grade code using Python, Go, Bash, or a similar language.
Strong understanding of Linux, networking, DNS, load balancing, and distributed systems.
Experience with monitoring, logging, tracing, and observability platforms.
Strong troubleshooting skills and the ability to investigate complex production issues.
Ability to work independently, take ownership, and drive projects from design through production.
Strong English communication skills and the ability to collaborate across multiple engineering teams.

AI Experience you have:
Hands-on experience using AI and Generative AI tools as part of software development, infrastructure, or operational workflows.
Experience working with LLM APIs, AI coding assistants, or AI automation tools.
Ability to identify processes that can be improved through AI and translate them into practical engineering solutions.
Understanding of prompt engineering, responsible AI usage, and the secure handling of sensitive information.
Experience with CAG, AI agents, RAG, MCP, LLM integrations, or AIOps solutions is an advantage.

Bonus points:
Experience working with data platforms, data infrastructure, or large-scale data processing systems.
Understanding of data pipelines, data ingestion, streaming systems, or distributed data architectures.
Experience operating large-scale, multi-region, or multi-account AWS environments.
Experience with GitOps tools such as Argo CD or Akuity.
Experience with service mesh, API gateways, or service discovery solutions.
Experience with Datadog, Prometheus, Grafana, OpenTelemetry, or similar observability tools.
Experience with cloud security, secrets management, and Vault.

Requirements:
What Were Looking For:



3+ years of experience as a Platform Engineer or a strong Backend Engineer with a DevOps focus.
Strong knowledge of CI/CD pipelines, versioning, and release management.
Proven experience with modern build tools (e.g., Bazel, SWC) and managing CI workflows (e.g., GitHub Actions, GitLab CI).
Good skills with infrastructure-as-code tools like Terraform and Helm.
Hands-on experience with Kubernetes, including containers (Docker), Kafka and cloud providers (AWS, GCP, or Azure).
Strong programming skills in Python, Go, TypeScript, or another modern backend language.
Experience with monorepo tools (Lerna, NX, PNPM) is a big plus.
Familiarity with GitOps workflows using tools like ArgoCD or Flux.
A strong sense of ownership and a passion for making systems reliable, scalable, and improving the developer experience.