AI Native Software Engineering - Senior Manager

Accenture; Riyadh; On-site; SAR 200,000 - 300,000; Full time

Job summary

A leading technology services company seeks an AI Native Engineer to design and enhance cloud-native solutions. You will engineer enterprise-ready AI agents and integrate platforms, driving intelligent automation in various sectors. Strong proficiency in Kubernetes, Docker, and AI platforms is essential. This role involves client engagement and may require travel depending on business needs.

Qualifications

• Experience with cloud-native solutions and AI-native engineering.
• Demonstrated ability in designing and deploying AI agents in enterprise settings.
• Strong analytical skills and ability to thrive in ambiguity.

Responsibilities

• Design and engineer enterprise-ready AI agents.
• Develop integration layers across various AI providers.
• Leverage cloud-native technologies to build scalable systems.
• Conduct workshops and engagements with clients to foster collaboration.

Skills

Cloud-native solutions engineering

Agent architecture and engineering

Containerization (Kubernetes, Docker)

Microservices design

CI/CD practices

Tools

Kubernetes

Docker

AI platforms (Anthropic, Google, OpenAI)

Job description

Accenture Technology:

Through unmatched industry experience, leading technologies from our ecosystem partners and startups, and the largest delivery network in the world, we provide a powerful range of capabilities that can be tailored to our client’s most complex business needs. With over 100 innovation hubs deployed around the world, we help clients continuously innovate at speed and at scale so they can outpace their peers. You will bring innovation, intelligence, and industry experience together with the newest technologies to help clients innovate at scale and transform their businesses. Visit us at www.accenture.com.

We are:

A forward-thinking services company at the forefront of AI-native innovation. We partner with enterprise clients to create next-generation, agent-powered workflows engineered to scale in real-world settings. Our engineers embed deeply with customers and move projects beyond experimentation into ಆಚ operational reality.

You are:

An AI Native Engineer with experience building cloud-native solutions, and deep expertise in designing and deploying agentic Sachen, especially for enterprise environments. You are a critical thinker that迈 thrives in ambiguity, delivering concrete results by designing, building, and running custom AI agents that augment workflows and scale across modern infrastructure. You’ll help shape the playbook for how enterprises adopt and scale AI-native engineering globally.

The Work:

You’ll embed directly with clients — acting as both technologist and trusted advisor. You’ll partner with派 stakeholders to define use cases, rapidly prototype, and deploy agentic workflows that are robust, secure, and operational in complex enterprise domains. Often, these will be completely new platforms and systems that need to be stitched together in our clients’ environments alongside our ecosystem partners.

Responsibilities:

• Agent Architecture and Engineering: Design and engineer enterprise-ready AI agents encompassing retrieval, orchestration, policy-based routing, tool invocation, evaluation harnesses, and lifecycle observability.
• AI Platform Integration: Develop abstraction layers across AI providers (Anthropic, Google, OpenAI, etc.) to enable seamless integration and enablement.
• Cloud-Native Engineering: Leverage containerization (Kubernetes, Docker), microservices, serverless, event-driven architectures, CI/CD, and observability to deliver scalable AI-native systems.
• Domain-Specific Workflows: Tailor and deploy agentic applications across verticals — e.g., finance, healthcare, retail — addressing domain-specific processes via intelligent automation.
• Client Engagement: Conduct design workshops, POCs, and code-with sessions to shape data-driven agent workflows with stakeholders, fostering trust and adoption.
ারণ লষণ
• Measure & Improve: Define and use key metrics, test threshes, and evaluation plans to measure agent accuracy, latency, safety, and cost effectiveness.
• Knowledge Sharing: Craft reusable patterns, documentation, and best practices to influence internal assets and client roadmaps.

Travel may be required for this role. The amount of travel will vary from 0 to 100% depending on business need and clientлох requirements.