Job description

KEY RESPONSIBILITIES: •Design, build, and own DevOps platforms and applications that leverage AI/ML to improve developer productivity, reliability, and security. •Architect, implement, and maintain solutions using modern DevOps, MLOps, and AIOps tools and practices, including LLMs, vector search, and AI-assisted automation. •Develop and enhance AI-powered features for CI/CD, observability, and incident management, including intelligent alerting, anomaly detection, and automated remediation workflows. •Lead and contribute to the development of automation scripts, tools, and services using Python (preferred) and other languages (TypeScript/JavaScript, Bash, Groovy) to integrate with REST and AI APIs. •Collaborate with cross-functional teams (software engineering, SRE, security, data, and platform teams) to define requirements, design scalable solutions, and drive adoption of DevOps and AI/ML best practices. •Implement and optimize CI/CD pipelines using systems such as GitHub Actions, Jenkins, Kubernetes, and Docker to ensure high reliability, security, and velocity of software delivery. •Use AI-driven observability and chatops to troubleshoot and resolve production issues, improve mean time to detection (MTTD) and mean time to resolution (MTTR), and enhance system resilience. •Champion and operationalize AI copilots, chatops, and knowledge-automation tools across teams to streamline workflows, reduce manual toil, and improve developer experience. •Establish and enforce standards for source control, code review, and policy-as-code (e.g., trunk-based development, code ownership, and automated quality/security gates). •Contribute to technical design reviews, documentation, and continuous improvement of DevOps and AI/ML-enabled platform capabilities. PREFERRED EXPERIENCE: •Hands-on experience with modern DevOps tooling and practices, including: oCI/CD platforms such as GitHub Actions and Jenkins oContainerization and orchestration with Docker and Kubernetes •Practical experience applying AI in DevOps, for example: oLLM-powered PR summarization, test generation, or issue triage oAnomaly detection on logs and metrics oChatops for incident response and operational support •Strong scripting and automation skills: oProficiency in Python oExperience with TypeScript/JavaScript, Bash, or Groovy is an asset oAbility to build small to medium-scale automations and integrate with REST and AI APIs •Solid understanding of source control and code review workflows: oExperience with GitHub, GitLab, Bitbucket, or Gerrit oFamiliarity with trunk-based development, codeowners, and policy-as-code enforcement •Experience with relational databases and SQL, with an understanding of database concepts, schema design, and performance considerations. •Knowledge of computer hardware components and experience installing, configuring, and troubleshooting hardware and software issues is a plus. •Demonstrated ability to work effectively in a fast-paced, collaborative engineering environment, with strong communication and interpersonal skills. ACADEMIC CREDENTIALS: •Bachelor’s or Master's degree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent.

Requirements

Must-haves

•Design, build, and own DevOps platforms and applications that leverage AI/ML to improve developer productivity, reliability, and security.
•Architect, implement, and maintain solutions using modern DevOps, MLOps, and AIOps tools and practices, including LLMs, vector search, and AI-assisted automation.
•Develop and enhance AI-powered features for CI/CD, observability, and incident management, including intelligent alerting, anomaly detection, and automated remediation workflows.
•Collaborate with cross-functional teams (software engineering, SRE, security, data, and platform teams) to define requirements, design scalable solutions, and drive adoption of DevOps and AI/ML best practices.
•Implement and optimize CI/CD pipelines using systems such as GitHub Actions, Jenkins, Kubernetes, and Docker to ensure high reliability, security, and velocity of software delivery.
•Use AI-driven observability and chatops to troubleshoot and resolve production issues, improve mean time to detection (MTTD) and mean time to resolution (MTTR), and enhance system resilience.
•Champion and operationalize AI copilots, chatops, and knowledge-automation tools across teams to streamline workflows, reduce manual toil, and improve developer experience.
•Establish and enforce standards for source control, code review, and policy-as-code (e.g., trunk-based development, code ownership, and automated quality/security gates).
•Contribute to technical design reviews, documentation, and continuous improvement of DevOps and AI/ML-enabled platform capabilities.
oProficiency in Python
oExperience with TypeScript/JavaScript, Bash, or Groovy is an asset
oAbility to build small to medium-scale automations and integrate with REST and AI APIs
•Solid understanding of source control and code review workflows:
oExperience with GitHub, GitLab, Bitbucket, or Gerrit
oFamiliarity with trunk-based development, codeowners, and policy-as-code enforcement

Nice-to-haves

•Lead and contribute to the development of automation scripts, tools, and services using Python (preferred) and other languages (TypeScript/JavaScript, Bash, Groovy) to integrate with REST and AI APIs.
•Hands-on experience with modern DevOps tooling and practices, including:
oCI/CD platforms such as GitHub Actions and Jenkins
oContainerization and orchestration with Docker and Kubernetes
•Practical experience applying AI in DevOps, for example:
oLLM-powered PR summarization, test generation, or issue triage
oAnomaly detection on logs and metrics
oChatops for incident response and operational support
•Knowledge of computer hardware components and experience installing, configuring, and troubleshooting hardware and software issues is a plus.

Application prep

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Keywords to mirror

aimlci/cdpythontypescriptjavascriptrestkubernetesdockersql

Platform: jobdiva
Effort: medium