1 day ago
Riyadh, Saudi ArabiaSenior
Responsibilities
- Design and build enterprise-ready AI agents with retrieval, orchestration, policy-based routing, tool invocation, evaluation harnesses, and lifecycle observability.
- Develop and deploy resilient agentic workflows and integrate multiple AI providers through abstraction layers, shared libraries, SDKs, and reusable engineering patterns.
- Build and operate scalable cloud-native systems using Kubernetes, Docker, microservices, serverless architectures, event-driven architectures, CI/CD, and observability stacks.
- Own production deployment, monitoring, troubleshooting, and continuous improvement of AI-native services.
- Adapt agentic applications to domain-specific workflows across industries such as finance, healthcare, and retail.
- Lead or participate in client workshops, proofs of concept, code-with sessions, technical discussions, and delivery activities.
- Define metrics and evaluation plans for agent accuracy, latency, safety, and cost effectiveness.
- Create documentation, best practices, reusable patterns, and internal knowledge-sharing materials.
Requirements
- Demonstrated engineering experience with cloud-native systems, APIs, microservices, containerization, and serverless architectures.
- Hands-on experience designing and deploying agentic solutions involving agents, orchestration, context engineering, retrieval-augmented generation, and workflow automation in production or near-production environments.
- Experience with AI platforms such as OpenAI, Claude, Vertex AI, or open-source models, including multi-provider AI pipeline abstraction layers.
- Strong Python, Java, or equivalent programming expertise, plus experience building 12-factor applications and infrastructure as code with tools such as Terraform and Helm.
- Proven client-facing communication and collaboration skills, including leading technical discussions, workshops, and delivery sessions.
- Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
- Relevant AI certifications or agentic tooling experience are preferred.
- Experience with Agentic or AI Engineering in enterprise environments, multi-agent orchestration, agent frameworks, compound AI systems, or agent registries is preferred.
- Experience with LangGraph, CrewAI, Claude SDK, OpenAI SDK, or comparable tooling is preferred.
- Experience delivering solutions across multiple industries and driving execution across multiple workstreams is preferred.
Benefits
- Travel may be required, varying from 25% to 75% based on business needs and client requirements.
Tech Stack
Categories
Solutions Engineering
About Accenture
Accenture is a global professional services firm providing management consulting, systems integration and technology, cybersecurity, and business process outsourcing for enterprises and governments. It operates a services-driven model delivering projects and managed services, often with major cloud and software partners, across industries worldwide. Headquartered in Dublin and publicly traded on the NYSE (ACN), it originated as Andersen Consulting and adopted the Accenture name in 2001.