Lima, Lima
Job Summary

DevOps Strategy and Platform Evolution
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Define and implement a modern DevOps and platform engineering strategy aligned with data and AI platform goals.
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Develop roadmaps that incorporate AI-assisted development, testing, and operations.
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Drive the evolution from traditional DevOps to intelligent, self-service platform capabilities.
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Continuously evaluate emerging technologies (e.g., GenAI, LLMOps, AIOps) and incorporate them where relevant.
AI-Enabled CI/CD and Automation
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Design and optimize CI/CD pipelines using AI-assisted tools (e.g., code generation, test generation, pipeline optimization).
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Integrate AI copilots and automation agents into development and deployment workflows.
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Implement intelligent quality gates (e.g., automated code reviews, anomaly detection in pipelines).
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Enable self-healing pipelines and automated failure diagnostics where possible.
Automation and Framework Enhancement
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Build scalable automation frameworks leveraging AI, scripting, and infrastructure as code.
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Automate repetitive tasks using AI agents, prompt-based workflows, or orchestration frameworks.
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Enhance DevOps pipelines to support data products and AI/ML workloads (MLOps/LLMOps).
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Standardize reusable templates and pipeline components for platform-wide adoption.
Data & AI Platform Integration
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Analyze and optimize integrations across the Anglo American Data Platform, including:
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Databricks (data processing, workflows, DABs)




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Airflow (orchestration)
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Azure services (compute, storage, identity)
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Power BI / downstream consumption layers
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Support deployment patterns for AI/ML models, feature pipelines, and inference services.
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Enable end-to-end lifecycle management for AI applications (training deployment monitoring).
Governance, Security, and Reliability
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Implement governance practices across pipelines, including policy-as-code and automated compliance checks.
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Manage access control and ensure secure DevOps practices across environments.
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Introduce AIOps practices for monitoring, alerting, and incident management.
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Ensure high availability, scalability, and observability of DevOps processes.
Documentation and Developer Experience
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Create and maintain clear documentation, including AI-assisted “how-to” guides and self-service enablement.
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Improve developer experience through intelligent tooling, chat-based interfaces, and automation.
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Promote adoption of DevOps and AI capabilities across teams.
Troubleshooting and Operational Support
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Collaborate with Data Delivery and platform teams to resolve issues efficiently.
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Use AI-assisted diagnostics and root cause analysis tools to accelerate incident resolution.
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Support production environments and ensure stability of pipelines and deployments.
Standards and Best Practices
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Define and promote best practices in DevOps, platform engineering, and AI-enabled delivery.
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Coach teams on adopting modern DevOps + AI approaches.
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Drive consistency and reuse across teams and projects.

Key Responsibilities
1. To design and develop new tools as per the client’s requirements and/ customize the existing tools.
2. To lead the technical design , ensuring alignment with business requirements, industry standards, and best practices, while determining the optimal configuration of modules, databases, interfaces, and integrations to support business processes.
3. To prepare capability presentations| assessments| proposal preparation.
4. To coordinate project management related activities like creating project plans, allocating resources, and coordinating activities among team members and stakeholders.
5. To support the professional growth and development of the consulting team members by training, and mentorship.

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