✦ Luna Orbit — AI & Machine Learning

AI Native Engineer - Reinvention Center

at Accenture

📍 St. Pete, 140 Fountain Pkwy, Tampa Corp Hybrid 💰 $73K – $261K USD / year Posted April 14, 2026
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Position Details

Salary $73K – $261K USD / year
Type Full-Time
Experience senior
Exp. Years Not specified
Education Not specified
Category AI & Machine Learning

About this role

Accenture seeks an AI Native Engineer to design, build, and deploy secure enterprise AI agentic systems for client environments. The role combines AI agent engineering with cloud-native platform integration and operational observability.

Key Responsibilities

  • Design and engineer enterprise-ready AI agents (retrieval, orchestration, policy-based routing, tool invocation, evaluation harnesses, lifecycle observability)
  • Build abstraction layers across AI providers (Anthropic, Google, OpenAI, etc.)
  • Deliver scalable AI-native systems using Kubernetes, Docker, microservices, serverless, event-driven architectures, CI/CD, and observability
  • Tailor agentic applications to domain-specific workflows across verticals
  • Conduct design workshops, POCs, and code-with sessions to prototype and deploy agentic workloads

Technical Overview

You will engineer enterprise-ready AI agents that include retrieval, orchestration, policy-based routing, tool invocation, evaluation harnesses, and lifecycle observability. You will also integrate multiple AI providers via abstraction layers and deploy cloud-native systems using containerization (Kubernetes, Docker), microservices, serverless, event-driven architectures, CI/CD, and observability.

Ideal Candidate

The ideal candidate is a senior AI Native Engineer with strong cloud-native engineering experience and deep expertise designing and deploying enterprise AI agentic systems. They can build robust AI agents (retrieval, orchestration, policy-based routing, tool invocation, evaluation, and lifecycle observability) and integrate multiple AI providers while deploying secure, operational solutions using Kubernetes and Docker.

Must-Have Skills

experience building cloud-native solutionsdeep expertise in designing and deploying agentic systemsdesign and engineer enterprise-ready AI agents encompassing retrievalorchestrationpolicy-based routingtool invocationevaluation harnessesand lifecycle observabilityDevelop abstraction layers across AI providers (AnthropicGoogleOpenAIetc. )Leverage containerization (KubernetesDocker)microservicesserverlessevent-driven architecturesCI/CDand observability

Tools & Platforms

KubernetesDockerCI/CDobservability

Required Skills

AI agentsretrievalorchestrationpolicy-based routingtool invocationevaluation harnesseslifecycle observabilityAI Platform IntegrationAnthropicGoogleOpenAIKubernetesDockermicroservicesserverlessevent-driven architecturesCI/CDobservabilitysecure deploymentPOCsdesign workshops

Hard Skills

AI agentsretrievalorchestrationpolicy-based routingtool invocationevaluation harnesseslifecycle observabilityAnthropicGoogleOpenAIabstraction layers across AI providerscontainerizationKubernetesDockermicroservicesserverlessevent-driven architecturesCI/CDobservabilitysecureoperational deploymentcloud-native solutionsagentic systemsrapid prototypingPOCscode-with sessions

Soft Skills

critical thinkingthrive in ambiguitytrusted advisorpartner with stakeholderscollaborationwork with clientsdesign workshops

Industry & Role

Industry Consulting
Job Function Design and deploy secure, operational enterprise AI agentic systems as a cloud-native platform engineer.
Role Subtype AI Engineer
Tech Domains Kubernetes, Docker, AI & Machine Learning, DevOps & SRE

Keywords for Your Resume

AI Native Engineeragentic systemscloud-native solutionsAI agentsretrievalorchestrationpolicy-based routingtool invocationevaluation harnesseslifecycle observabilityAI Platform IntegrationAnthropicOpenAICI/CDKubernetesDockermicroservicesserverlessevent-driven architecturesobservabilityenterprise-readysecurePOCsdesign workshopscode-with sessions

Deal Breakers

Must have deep expertise designing and deploying agentic systems, Must be able to engineer enterprise-ready AI agents with retrieval, orchestration, policy-based routing, tool invocation, evaluation harnesses, and lifecycle observability, Must have cloud-native engineering skills including Kubernetes and Docker, Must have experience integrating AI providers (Anthropic, Google, OpenAI)

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