This role pays less than
72%
of similar roles. Most pay
$145,000–$205,375
— the shaded band above.
At the midpoint, this role pays about
$147k
versus about
$175k
for comparable roles.
Based on 240 similar postings.
Employer
About Accenture
Accenture is a leading global professional services company specializing in IT, strategy, consulting, and operations, with a strong focus on digital transformation, cloud computing, and artificial intelligence.
Accenture currently has
184 open roles
on FindRole.
Listed pay typically runs
$94,400–$266,300
across 160 roles with salary data.
As an Agentic Operations Engineer, you will join the team to design, develop, and implement multi-agent AI solutions using LLMs, orchestration frameworks, and enterprise integration patterns. You will build and maintain conversational AI applications, agent workflows, memory management, tool integrations, and decision-making capabilities across distributed agent ecosystems while collaborating with product, architecture, and engineering teams. The role requires extensive experience in Python and Java to develop generative AI and agent-based applications using frameworks like LangGraph, LangChain, Semantic Kernel, AutoGen, or CrewAI. You will work with REST APIs, microservices, cloud-native applications, Git, CI/CD pipelines, and tools like GitHub Copilot or Cursor. Key technical focuses include RAG solutions, vector databases, prompt engineering, and containerization via Docker and Kubernetes to solve complex problems in distributed agent ecosystems and enterprise systems.
Design, develop, and implement multi-agent AI solutions using LLMs and orchestration frameworks.
Build and maintain conversational AI applications with integrated memory management and tool capabilities.
Develop scalable AI-powered solutions in collaboration with product, architecture, and engineering teams.
Utilize AI-assisted development tools to improve code quality and delivery speed.
Integrate enterprise systems with AI platforms using REST APIs and microservices.
Implement RAG solutions, vector databases, and autonomous workflows in cloud environments.
Apply prompt engineering and evaluation frameworks to ensure responsible AI practices.
What we're looking for
Minimum of 7 years of software engineering experience with hands-on expertise in Python and Java.
Minimum of 2 years of experience developing AI/ML, Generative AI, conversational AI, or agent-based applications using frameworks like LangChain or LangGraph.
Experience designing REST APIs, microservices, cloud-native applications, and integrating enterprise systems with AI platforms.
Proficiency with Git, CI/CD pipelines, and AI-assisted development tools such as GitHub Copilot or Cursor.
High School Diploma or GED.
Bachelor's degree in Computer Science, Engineering, Information Technology, or a related field (preferred).
Experience with RAG solutions, vector databases, and multi-agent orchestration in cloud environments like Azure, AWS, or GCP (preferred).
Knowledge of prompt engineering, conversation design, AI governance, containerization (Docker, Kubernetes), and modern software architecture (preferred).