AI Engineer
- Discuss this with your agent
- Open in Claude
- Open in ChatGPT
Prepare application
- Draft this with your agent
- Open in Claude
- Open in ChatGPT
Role details
Tech stack
Job description
You build the systems that actually make AI work in enterprise environments, not demos, not prototypes that stall after a pilot, but production agentic architectures running inside real client organizations. The difference between an AI Engineer and what we are looking for is straightforward: you have shipped a multi-agent system in production, you have owned the eval harness, and you know what happens when your agent fails at 2am because you have lived it. As an AI Engineer (Agentic/Applied), you will design, build, and deploy production-grade agentic AI systems across the full enterprise technology stack. You will work directly with client engineering teams, lead technical design sessions, and build reusable patterns and accelerators that scale beyond individual engagements. This role sits at the heart of the AI engineering talent market - demand is growing faster than supply and will continue to do so. We offer what no single product company can: breadth across every industry, every, build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services-creating tangible value at speed and scale. We are a talent- and innovation-led company with approximately 791,000 people serving clients in more than 120 countries. Technology is at the core of change today, and we are one of the world’s leaders in helping drive that change, with strong ecosystem relationships. We combine our strength in technology and leadership in cloud, data and AI with unmatched industry experience, functional expertise and global delivery capability. Our broad range of services, solutions and assets across Strategy & Consulting, Technology, Operations, Industry X and Song, together with our culture of shared success and commitment to creating 360° value, enable us to help our clients reinvent and build trusted, lasting relationships. We measure our success by the 360° value we create for our clients, each other, our shareholders, partners and communities. Visit us at www.accenture.com Declaración de igualdad de oportunidades en el empleo Creemos que nadie debe ser discriminado por sus diferencias. Todas las decisiones de empleo se tomarán sin importar la edad, raza, credo, color, religión, sexo, origen nacional, ascendencia, discapacidad, condición de veterano militar, orientación sexual, identidad o expresión de género, información genética, estado civil, ciudadanÃa ni ningún otro criterio protegido por la legislación aplicable. Nuestra rica diversidad nos hace más innovadores, competitivos y creativos, lo que nos ayuda a servir mejor a nuestros clientes y comunidades.
Requirements
standards, safety monitoring and cost controls across multiple concurrent systems Lead client engineering engagements at senior level - facilitate architecture design sessions, lead proof-of-concept delivery, and drive alignment between client technology leadership and delivery teams Shape and publish reusable patterns, accelerators, and engineering standards that scale across the practice and reduce ramp-up time on new client engagements Own the measurement framework for agentic system quality: define accuracy, latency, safety, and cost metrics; present programme-level AI impact in business terms to senior client stakeholder Job Qualification: Hands-on experience designing and deploying agentic AI solutions in a production environment - non-negotiable Demonstrated experience with agentic orchestration frameworks: LangGraph, CrewAI, AutoGen, or equivalent - at production depth, not tutorial level Direct experience calling LLM APIs (OpenAI, Anthropic, Vertex AI) in production code
About the company
provider abstraction, token management, latency and cost tradeoffs RAG pipeline ownership: embeddings, chunking strategy, vector databases, and context engineering LLMOps fundamentals: eval harness design, prompt versioning, and production observability Cloud-native engineering maturity: Kubernetes, Docker, microservices, serverless, CI/CD, and IaC (Terraform or Helm) Strong Python; Java or equivalent backend language acceptable; production debugging and observability experience Quality of experience is weighted over years, a candidate who has shipped three production agentic systems in four years is preferred over a generalist with passive AI exposure People lead responsibilities: experience managing, developing, and performance-managing a team of engineers; setting individual development plans and conducting career conversations About Accenture Accenture is a leading global professional services company that helps the world’s leading businesses, governments and other organizations
Apply for this position
This job is hosted externally. Click below to view the full posting and apply.
Prepare application
- Draft this with your agent
- Open in Claude
- Open in ChatGPT
Good distractions
Talks and stories from around this role — technically off-topic, practically not.
Moments
Explore playlistsVideos
See allRelated articles
See all
Navigating the AI Shift
What is Agentic Programming and Why Should Developers Care?
MLOps And AI Driven Development
Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?