Agentic DevOps Lead
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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.
- Minimum of 8 years in technical leadership roles, including DevOps, AI/ML, or cloud-native engineering.
- Minimum of 3 years of python experience.
- Minimum of 1 year of proven experience with LLMs, agentic frameworks (E.g. LangGraph, Crew AI, Autogen), prompt engineering
- Minimum of 6 years of Hands-on expertise in CI/CD, containerization (Docker, Kubernetes), and infrastructure-as-code (Terraform).
- Minimum of 6 years' experience in architecting solutions on Azure.
- Minimum of 1 year of Experience deploying and monitoring Generative AI systems in production.
- Minimum of 1 year of experience with RAG, LLM fine-tuning, and multi-agent orchestration.
- Bachelor's degree or equivalent (minimum 12 years) work experience. (If Associate's Degree, must have minimum 6 years work experience
- Exposure to enterprise data integration (e.g., SAP, SharePoint).
- Certifications in cloud architecture (AWS, Azure, GCP, Oracle) or AI/ML.
- Cloud engineering on AWS and GCP preferred.
- Strong understanding of cloud security, observability, and cost optimization strategies.
- Prior experience in life sciences, fintech, or regulated industries is a plus.
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