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Collaborating with Engineers and Scientists in the organization to construct complex data sources for algorithms and machine learning models.
Job Responsibility:
Design, implement, and evolve cloud-native solutions for infrastructure provisioning, configuration management, and deployment pipelines
Own production systems end-to-end, including design decisions, implementation, operational reliability, and iterative improvement
Develop and maintain Infrastructure as Code and Configuration as Code using tools such as Terraform, CloudFormation, and Ansible
Design, implement, optimize, and own CI/CD pipeline tooling for application and infrastructure deployments using tools such as GitHub Actions or Jenkins
Design, implement, and own high‑quality, maintainable code in a modern language like Python, and author reliable Bash or PowerShell scripts
Use AI-assisted development tools (e.g., GitHub Copilot) and contribute to internal platforms that enable teams to build and deploy AI-enabled solutions using AWS Bedrock and WatsonX
Implement observability, monitoring, and alerting to ensure system reliability, scalability, performance, and cost efficiency
Embed security into infrastructure and delivery workflows by applying DevSecOps practices such as least-privilege access, secure defaults, and automated policy enforcement
Collaborate effectively with application, platform, network, and security teams, clearly communicating requirements, tradeoffs, and design decisions
Maintain clear documentation and proactively explore and apply emerging technologies in cloud, DevOps, and AI
Requirements:
Software engineering skills in Python (preferred) and Bash
Experience with Web development, Java, JavaScript, and/or PowerShell desirable
Hands-on experience building and operating AWS-based systems using services such as EC2, ECS/EKS, RDS, S3, and Lambda
Experience using Infrastructure as Code and Configuration as Code tools (Terraform, CloudFormation, Ansible)
Experience building and operating CI/CD pipelines in production environments
Knowledge of containerization and orchestration technologies, including Docker and Kubernetes
Working knowledge of AWS networking and security, including troubleshooting connectivity issues, defining security group rules, applying least-privilege IAM policies, and partnering with network and security engineers
Ability to impact reliability, scalability, and performance, and make pragmatic tradeoffs in production systems
Strong collaboration and communication skills, with the ability to influence technical outcomes across teams
Demonstrated self-directed learning and curiosity—proactively seeking out and applying new technologies and approaches
3+ years of experience in software development, cloud engineering, or DevOps roles
Experience operating automated infrastructure and delivery pipelines at scale
Exposure to foundational AI concepts (e.g., LLMs, agentic patterns, RAG) and interest in applying AI to automation, developer tooling, or operational workflows
Contributions to open-source projects
AWS certification or equivalent cloud credentials
Familiarity with multi-cloud environments (AWS, Azure, GCP)
Experience working in Agile environments (Scrum or Kanban)
Nice to have:
Contributions to open-source projects
AWS certification or equivalent cloud credentials
Familiarity with multi-cloud environments (AWS, Azure, GCP)
Experience working in Agile environments (Scrum or Kanban)