Accenture
Agentic DevOps Lead – Data & AI
- Permanent
- Dubai, United Arab Emirates
- Experience 2 - 5 yrs
Job expiry date: 28/05/2026
Job overview
Date posted
13/04/2026
Location
Dubai, United Arab Emirates
Salary
AED 20,000 - 30,000 per month
Compensation
Job description
Accenture Technology delivers unmatched industry experience, leading technologies from ecosystem partners and startups, and operates the largest delivery network in the world with over 100 innovation hubs globally, enabling clients to continuously innovate at speed and scale. Within Accenture’s Data & AI organization, supported by a $3B investment and over 45,000 Data & AI professionals, this role operates in the emerging Data & AI decade focused on optimizing and reinventing businesses using data and AI. As an Agentic DevOps Lead – Data & AI operating within Artificial Intelligence and Machine Learning Computational Science, the role formulates real-world problems into scalable AI and Machine Learning solutions and develops cutting-edge artificial intelligence systems leveraging machine learning, deep learning, and data analysis. The position leads Agentic DevOps initiatives focused on scaling Generative AI agentic solutions across diverse cloud environments and architecting a reusable, portable Agentic DevOps framework. The role operationalizes frameworks ensuring production readiness, observability, deployment efficiency, and enterprise-grade standards for agentic applications. Responsibilities include defining scalable DevOps frameworks using LangGraph, Crew AI, Autogen, and other orchestration tools; building reusable scaffolding for agent lifecycle management, orchestration, monitoring, and metering; architecting and managing CI/CD pipelines for cloud-native deployment across public and private cloud environments including AWS, Microsoft Azure, and Google Cloud Platform (GCP); ensuring security, reliability, and compliance for production deployments; and collaborating with cross-functional teams including engineers, architects, DevOps specialists, AI engineering teams, and solution architects to tailor deployments and support client onboarding. The role leads teams delivering robust, scalable, and client-ready agentic systems, enabling innovation, intelligence, and transformation for enterprise clients at global scale.
Required skills
Key responsibilities
- Lead the design, definition, and execution of Agentic DevOps strategy by developing scalable DevOps frameworks for agentic systems using LangGraph, Crew AI, Autogen, and orchestration tools while ensuring alignment with enterprise architecture standards, Generative AI adoption strategies, and client-specific deployment requirements across diverse industries and business environments
- Architect and operationalize reusable Agentic DevOps frameworks and scaffolding that support agent lifecycle management, orchestration, monitoring, and metering capabilities while ensuring portability, extensibility, and maintainability across multiple public and private cloud environments
- Design, implement, and manage cloud-native deployment strategies and CI/CD pipelines across AWS, Microsoft Azure, and Google Cloud Platform (GCP) environments to support automated build, testing, deployment, versioning, rollback, and release management for agentic applications
- Ensure production readiness for agentic applications by implementing enterprise-grade standards for security, reliability, availability, compliance, observability, logging, monitoring, and performance optimization across all deployment environments
- Lead and mentor cross-functional teams including engineers, architects, DevOps specialists, AI engineers, and client enablement professionals to deliver robust, scalable, and client-ready agentic systems aligned with Accenture’s Data & AI transformation objectives
- Collaborate with solution architects and client stakeholders to tailor Agentic DevOps deployments to specific client environments while ensuring seamless onboarding, operationalization, and knowledge transfer for production deployment of agentic solutions
- Drive continuous improvement initiatives for Agentic DevOps frameworks by optimizing deployment efficiency, improving automation capabilities, enhancing monitoring and metering solutions, and scaling Generative AI agentic systems across enterprise environments
- Coordinate with Data & AI teams, cloud engineering teams, and enterprise stakeholders to ensure alignment between AI model deployment, DevOps frameworks, cloud-native architecture, and operational governance for scalable agentic applications
Experience & skills
- Demonstrate extensive experience in Generative AI, Agentic DevOps, Artificial Intelligence, Machine Learning, Deep Learning, and Data Analysis with the ability to formulate real-world problems into scalable AI and Machine Learning solutions across enterprise environments
- Possess hands-on expertise designing and implementing scalable DevOps frameworks, reusable scaffolding, and agent lifecycle management solutions using LangGraph, Crew AI, Autogen, and orchestration tools within enterprise-grade deployments
- Demonstrate strong experience architecting and managing CI/CD pipelines, cloud-native deployment models, and automated release management processes across AWS, Microsoft Azure, and Google Cloud Platform (GCP) public and private cloud environments
- Show proven ability to ensure production readiness by implementing enterprise-grade security, reliability, compliance, observability, logging, monitoring, and performance optimization standards for agentic applications and AI-driven systems
- Possess experience leading cross-functional teams including DevOps engineers, AI engineers, architects, and client enablement teams while delivering scalable Generative AI agentic solutions and enterprise-grade deployment frameworks
- Demonstrate expertise in designing portable and reusable DevOps frameworks capable of scaling agentic systems across multiple environments while supporting monitoring, metering, orchestration, and lifecycle management requirements
- Show ability to collaborate with solution architects and client stakeholders to tailor deployments, enable client onboarding, and support operationalization of agentic applications across enterprise client environments
- Possess strong understanding of cloud-native architecture, DevOps best practices, AI deployment strategies, and enterprise governance requirements for delivering robust, scalable, and production-ready agentic systems