Accenture

Accenture

Posted via Workday

AI Native Engineer

Posted Sep 23, 2026

Role at a glance

Salary
Not Disclosed
Location
Paris
Work arrangement
Hybrid
Employment
Full-time

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Role Summary

AI-generated

The AI Engineer (Agentic/Applied) designs, builds, and deploys production-grade agentic AI systems across enterprise technology stacks. The role works directly with client engineering teams to deliver agentic solutions and develops reusable patterns and accelerators for future engagements.

What You'll Do

  • Design and build production-grade agentic systems, including multi-agent orchestration, RAG pipelines, policy-based routing, tool...
  • Build and own RAG pipelines covering embeddings, chunking strategy, vector search, context window engineering, and quality tuning
  • Integrate and abstract across multiple LLM providers with fallback routing and token, cost, and latency management
  • Implement LLMOps with eval harnesses, prompt versioning, observability tooling, and cost and safety monitoring
  • Embed with client engineering teams through workshops, proofs of concept, code-with sessions, and architecture walkthroughs
  • Define and use metrics for agent accuracy, latency, safety, and cost-effectiveness, and present findings to client stakeholders

Generated from the employer's posting. Verify important details before applying.

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Qualifications

Hands-on production experience with agentic AI solutions; agentic orchestration frameworks such as LangGraph, CrewAI, AutoGen, or equivalent; production LLM API integration with OpenAI, Anthropic, or Vertex AI; RAG pipelines; LLMOps; Kubernetes, Docker, microservices, serverless, CI/CD, and IaC with Terraform or Helm; strong Python or Java; production debugging and observability.

Required

  • Minimum 1 year of hands-on experience designing and deploying agentic AI solutions in a production environment
  • Demonstrated experience with agentic orchestration frameworks: LangGraph, CrewAI, AutoGen, or equivalent
  • Direct experience calling LLM APIs (OpenAI, Anthropic, Vertex AI) in production code
  • 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

Preferred

  • A candidate who has shipped three production agentic systems in four years is preferred over a generalist with passive AI exposure

Original job description

Content provided by the employer

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 enterprise technology stack, and every level of organizational complexity, combined with vendor fellowship access inside Anthropic, OpenAI, Microsoft, and Google engineering teams and a direct pathway to the Forward Deployed Engineer programme. 

 

Key Responsibilities 

  • Design and build production-grade agentic systems end-to-end: multi-agent orchestration, RAG pipelines, policy-based routing, tool invocation, memory management, and lifecycle observability 
  • Build and own RAG pipelines: embeddings, chunking strategy, vector search, context window engineering and tuning against real quality targets 
  • Integrate and abstract across multiple LLM providers — OpenAI, Anthropic, Vertex AI, and open-source models — with fallback routing, token, cost, and latency management 
  • Implement LLMOps in production: eval harnesses with real quality metrics, prompt versioning, observability tooling (LangSmith, Braintrust, or equivalent), cost and safety monitoring 
  • Embed directly with client engineering teams to design, prototype, and deploy agentic solutions — workshops, proofs of concept, code-with sessions, and architecture walkthroughs 
  • Build reusable patterns, accelerators, and playbooks that scale beyond the individual client engagement and enable the next one to start faster 
  • Define and use metrics to measure agent accuracy, latency, safety, and cost-effectiveness; present findings and recommendations to client stakeholders in business terms

#LI-EU

  • 2 to 5 years of software engineering experience in production environments 
  • Minimum 1 year of 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: 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 

About Accenture

Accenture is a leading global professional services company that helps the world’s leading businesses, governments and other organizations 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 

Déclaration d'égalité des chances en matière d'emploi

Nous pensons que personne ne devrait être discriminé en raison de ses différences. Toutes les décisions d'embauche doivent être prises sans distinction d'âge, d'origine ethnique, de croyance, de couleur, de religion, de sexe, d'origine nationale, d'ascendance, de handicap, de statut d'ancien combattant, d'orientation sexuelle, d'identité ou d'expression de genre, d'informations génétiques, de statut matrimonial, de citoyenneté ou de tout autre critère protégé par la loi applicable. Notre riche diversité nous rend plus innovants, plus compétitifs et plus créatifs, ce qui nous permet de mieux servir nos clients et nos communautés.

 

Accenture

About the company

Accenture

Large Enterprise

Accenture is a global professional services company that specializes in providing consulting, technology, and outsourcing services. With a diverse range of industries served, including financial services, healthcare, and telecommunications, Accenture leverages advanced technologies and data analytics to help organizations improve their performance and drive innovation. Committed to sustainable progress, the company emphasizes its dedication to inclusivity, digital transformation, and building a more sustainable future for its clients and communities. With a presence in over 120 countries, Accenture is known for its expertise in integrating cutting-edge solutions that address complex business challenges.