"We Are The beginning of a new Data & AI decade that will reshape work and society has begun. Accenture is stepping boldly into this future with a clear strategy and purpose: to help clients optimize and reinvent their business with data & AI — backed by a $3B investment and commitment to our people to do industry-defining work.
With over 45,000 professionals dedicated to Data & AI, Accenture’s Data & AI organization brings together our Experienced Innovation, Strategic Investment, Exceptional Talent, and Power Ecosystem.
You Are
As an Artificial Intelligence and Machine Learning Computational Science professional, you will play a pivotal role in formulating real-world problems into practical, efficient, and scalable AI and Machine Learning solutions. You will be responsible for developing and implementing cutting-edge artificial intelligence solutions that drive innovation and enhance performance. You will collaborate with cross-functional teams and leverage your expertise in machine learning, deep learning, and data analysis to solve complex problems and deliver impactful AI-driven solutions.
The Work
We are seeking an experienced Agentic DevOps Lead to lead our Agentic DevOps initiatives. This role is pivotal in scaling our Generative AI agentic solutions across diverse cloud environments. You will architect and operationalize a reusable, portable Agentic DevOps framework that ensures production readiness, observability, and deployment efficiency for agentic applications.
You will lead a team of reinventors—engineers, architects, and DevOps specialists—focused on delivering industry-leading agentic systems that are robust, scalable, and client-ready.
Key Responsibilities
* Lead Agentic DevOps Strategy: Define and implement scalable DevOps frameworks for agentic systems using LangGraph, Crew AI, Autogen, and other orchestration tools.
* Framework Development: Build reusable scaffolding for agent lifecycle management, orchestration, monitoring, and metering.
* Cloud-Native Deployment: Architect and manage CI/CD pipelines for public and private cloud environments (AWS, Azure, GCP).
* Production Readiness: Ensure agentic applications meet enterprise-grade standards for security, reliability, and compliance.
* Team Leadership: Mentor and manage cross-functional teams across DevOps, AI engineering, and client enablement.
* Client Enablement: Collaborate with solution architects to tailor deployments for client environments and ensure seamless onboarding.
Travel may be required for this role. The amount of travel will vary from 0 to 100% depending on business need and client requirements.
Design and develop artificial intelligence AI and machine learning ML systems leveraging existing cloud AI services. Design and build scalable data pipelines to support model training and production with DevOps MLOps. Customize and apply Deep Learning and Gen AI models for use cases based on the business needs, data availability, system and infrastructure requirements including edge devices and High Performance Computers HPCs. Justify the quality and value of the solution. Engage in research and development of new AI and high performance compute algorithms, models, and simulations along with their applications to solve complex problems. Work with large scale datasets and utilize data preprocessing techniques to ensure high quality input for training and production. Implement and maintain efficient data storage and retrieval mechanisms for models and knowledge using appropriate tools.
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