About the role

AI summarised

The Agentic Platform Deployment & Maintenance Engineer at Accenture is responsible for deploying, configuring, and operating the enterprise agent platform in production. This role involves managing agent runtime services, optimizing performance, and ensuring reliable, observable, and secure operation of multi-agent workloads across environments. The engineer collaborates with platform engineers, AI engineers, and SREs to troubleshoot issues and refine deployment patterns.

BusinessFull-timeOther Functions

Key Responsibilities

Deploy, configure, and maintain the enterprise agent platform across development, staging, and production environments
Set up and manage managed agent runtime services, including provisioning, scaling, security, and lifecycle management
Design, maintain, and optimize agent runtime infrastructure (e.g., Python services on Docker/Kubernetes) for reliability and performance
Implement and manage agent registries for versioning, configuration, and controlled rollout of agents and shared components
Develop and maintain shared agent tooling and libraries to drive consistency, reuse, and operational efficiency across teams
Build and operate monitoring dashboards and alerts for agent and platform health using observability tools (e.g., Datadog, LangSmith, or equivalents)
Collaborate with platform engineers, AI engineers, and SREs to troubleshoot issues, tune performance, and refine deployment patterns
Contribute to API and service development to integrate the agent platform with upstream and downstream enterprise systems

Requirements

Strong hands-on experience with Python in a production environment
Experience deploying and operating containerized workloads using Docker and Kubernetes
Familiarity with agent frameworks and orchestration tools (e.g., LangChain, LangGraph, or similar)
Proven background in platform engineering, including environment configuration, automation, and performance tuning
Experience implementing monitoring, logging, and alerting for distributed systems and services
Solid understanding of API development and integration patterns in enterprise environments
Strong problem-solving and collaboration skills, with the ability to work closely with cross-functional engineering and product teams
Experience operating enterprise-scale AI, agent, or workflow platforms
Knowledge of best practices for runtime isolation, security, and access control in multi-tenant platforms
Familiarity with infrastructure-as-code and CI/CD pipelines for platform deployment and updates
Exposure to observability stacks such as Datadog, OpenTelemetry, or similar tools for metrics and tracing
Contributions to internal or open-source tooling related to agent frameworks, platform engineering, or monitoring