Development and Operations Engineer II
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What you'll do
- Create, maintain, and enhance automated product and AI/ML model deployments.
- Develop, modify, support, and maintain AWS-based components through Infrastructure as Code and automation (IaC).
- Enhance availability and incident management by implementing AI-driven observability and self-healing solutions based on predictive alerts.
- Continuously improve monitoring, logging, and AIOps capabilities, enabling us to be proactive instead of reactive.
- Conduct risk assessments and business impact analyses to identify potential threats and their impact on business operations and AI workflows.
- Design and configure DR solutions on AWS, including backup, replication, and failover strategies for infrastructure and vector/data stores utilizing services such as AWS Backup, AWS Elastic Disaster Recovery, and Lambda.
- Maintain and improve the current CI/CD and MLOps pipelines (GitHub Workflows & Jenkins).
- Utilize strong Python knowledge for operational automation, API integration, and AI workflow support.
- Apply proficiency in Terraform for Infrastructure as Code to manage AWS resources (including compute, storage, and GPU/EKS clusters).
- Write Shell and PowerShell scripts for system automation.
- Execute application and AI model deployment automation using Ansible, Terraform, Kubernetes, and model-serving frameworks.
- Review and maintain IaC repositories in Bitbucket and GitHub.
What they're looking for
- Experience in a similar role within a large-scale enterprise environment working with DevOps or MLOps practices.
- 3 to 5 years of experience with monitoring and AIOps solutions (DataDog, Grafana, Nagios, New Relic).
- Proficiency with container technologies like Docker, Kubernetes, ECS, EKS, and model-serving runtimes.
- Familiarity with AI/ML infrastructure components, AWS SageMaker, vector databases, or LLM deployment frameworks.
- Strong knowledge of AWS services related to DR, including AWS Backup, AWS Elastic Disaster Recovery, Lambda, etc.
- Experience with Infrastructure as Code (IaC) tools such as AWS CloudFormation or Terraform.
- Familiarity with networking, security, and storage solutions on AWS tailored for high-performance AI workloads.
- Excellent problem-solving skills and attention to detail.
- Ability to work independently and as part of a team.
Nice to have
- AWS certifications such as Certified Solutions Architect or Certified DevOps Engineer preferred.
- Monitoring tools setup experience using Datadog, Grafana, etc. preferred.
- Working experience or strong foundational understanding of core AI competencies, including Agentic AI, Retrieval-Augmented Generation (RAG), Model Context Protocol (MCP), custom Skills creation, and Large Language Models (LLMs).
- Practical hands-on experience utilizing AI-assisted developer tools and environments, such as VS Code, GitHub Copilot, Gemini, and Cursor, to enhance productivity and automate infrastructure workflows.
Summarised by NextRaise from the employer’s description, which follows in full below.
Full description from employer
Your Title: AI DevOps Engineer II
Job Location: Chennai, India
Our Department: Trimble Cloud xOps
As a member of Trimble’s global engineering team focused on accelerating Cloud Support, your first assignment will be to work on the Trimble Cloud xOps. You will be a key member of the Cloud Engineering Team committed to developing, automating, and supporting Trimble's cloud and AI projects while ensuring an intuitive product experience for our current and future customers. We are seeking a highly skilled, motivated, and collaborative individual who maintains a low-key demeanor. The ideal candidate should have experience in building responsive, customer-facing applications and scaling AI/ML infrastructure using the latest cloud and MLOps technologies.
What You Will Do:
Technical/Operational/Functional Expertise:
Create, maintain, and enhance automated product and AI/ML model deployments.
Develop, modify, support, and maintain AWS-based components through Infrastructure as Code and automation (IaC).
Enhance availability and incident management by implementing AI-driven observability and self-healing solutions based on predictive alerts.
Continuously improve monitoring, logging, and AIOps capabilities, enabling us to be proactive instead of reactive.
Conduct risk assessments and business impact analyses to identify potential threats and their impact on business operations and AI workflows.
Design and configure DR solutions on AWS, including backup, replication, and failover strategies for infrastructure and vector/data stores utilizing services such as AWS Backup, AWS Elastic Disaster Recovery, and Lambda.
Maintain and improve the current CI/CD and MLOps pipelines (GitHub Workflows & Jenkins).
Utilize strong Python knowledge for operational automation, API integration, and AI workflow support.
Apply proficiency in Terraform for Infrastructure as Code to manage AWS resources (including compute, storage, and GPU/EKS clusters).
Write Shell and PowerShell scripts for system automation.
Execute application and AI model deployment automation using Ansible, Terraform, Kubernetes, and model-serving frameworks.
Review and maintain IaC repositories in Bitbucket and GitHub.
Manage end-to-end deployments and AI/ML infrastructure pipelines.
Meet and achieve goals for Key Performance Indicators, Service Level Agreements, and Operating Level Agreements.
Maintain high levels of system uptime and model availability.
Create, define, manage, track, and improve processes to ensure effective, automated services are being provided.
What Skills & Experience You Should Bring:
AWS certifications such as Certified Solutions Architect or Certified DevOps Engineer preferred.
Experience in a similar role within a large-scale enterprise environment working with DevOps or MLOps practices.
3 to 5 years of experience with monitoring and AIOps solutions (DataDog, Grafana, Nagios, New Relic).
Proficiency with container technologies like Docker, Kubernetes, ECS, EKS, and model-serving runtimes.
Familiarity with AI/ML infrastructure components, AWS SageMaker, vector databases, or LLM deployment frameworks.
Strong knowledge of AWS services related to DR, including AWS Backup, AWS Elastic Disaster Recovery, Lambda, etc.
Experience with Infrastructure as Code (IaC) tools such as AWS CloudFormation or Terraform.
Familiarity with networking, security, and storage solutions on AWS tailored for high-performance AI workloads.
Excellent problem-solving skills and attention to detail.
Ability to work independently and as part of a team.
Monitoring tools setup experience using Datadog, Grafana, etc. preferred.
Working experience or strong foundational understanding of core AI competencies, including Agentic AI, Retrieval-Augmented Generation (RAG), Model Context Protocol (MCP), custom Skills creation, and Large Language Models (LLMs).
Practical hands-on experience utilizing AI-assisted developer tools and environments, such as VS Code, GitHub Copilot, Gemini, and Cursor, to enhance productivity and automate infrastructure workflows.
Key Result Areas:
Accountability for assignments, timely delivery, and meeting or exceeding quality requirements.
Continuous reduction of operational overhead through automated workflows and AIOps implementation.
How to Apply: Please submit an online application for this position by clicking on the ‘Apply Now’ button located in this posting.
Join a Values-Driven Team: Belong, Grow, Innovate.
At Trimble, our core values of Belong, Grow, and Innovate aren't just words—they're the foundation of our culture. We foster an environment where you are seen, heard, and valued (Belong); where you have an opportunity to build a career and drive our collective growth (Grow); and where your innovative ideas shape the future (Innovate). We believe in empowering local teams to create impactful strategies, ensuring our global vision resonates with every individual. Become part of a team where your contributions truly matter.
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