AI Native Engineer (Agentic / Applied)

Accenture; Madrid; Presencial; EUR 65.000 - 85.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

25 days vacation per year

Private medical insurance

3 extra leave days for charity work

Descripción de la vacante

Accenture is seeking an AI Engineer (Agentic/Applied) to design and build production-grade AI systems for enterprise environments. This role involves collaborating with client engineering teams and leading technical sessions to ensure scalability and quality of AI implementations.

The ideal candidate will have substantial experience in software engineering, particularly in deploying agentic AI solutions, and will possess strong management skills. Accenture offers a competitive salary alongside an extensive benefits package including vacation days and private medical insurance.

Formación

• Several years of software engineering experience in production environments.
• Hands-on experience designing and deploying agentic AI solutions.
• Experience with agentic orchestration frameworks.
• Direct experience calling LLM APIs in production code.
• RAG pipeline ownership and context engineering.
• Experience in LLMOps fundamentals.
• Cloud-native engineering maturity.
• Strong Python and production debugging experience.
• Experience managing and developing a team of engineers.

Responsabilidades

• Architect and govern production-grade agentic systems at enterprise scale.
• Lead client engineering engagements and architecture design sessions.
• Define RAG pipeline standards and establish quality benchmarks.
• Set multi-LLM integration standards and documentation.
• Own LLMOps strategies across multiple systems.
• Shape and publish reusable patterns and mentoring standards.
• Own the measurement framework for agentic system quality.

Conocimientos

Software engineering experience

Agentic AI solutions deployment

LLM API usage

RAG pipeline ownership

Cloud-native engineering

Python programming

Team management

Herramientas

Kubernetes

Docker

Terraform

Descripción del empleo

Accenture is a leading global professional services company, providing a broad range of services in strategy and consulting, interactive, technology and operations, with digital capabilities across all of these services. With our thought leadership and culture of innovation, we apply industry expertise, diverse skills and next-generation technology to each business challenge.

We believe in inclusion and diversity and supporting the whole person. Our core values comprise of Stewardship, Best People, Client Value Creation, One Global Network, Respect for the Individual and Integrity. Year after year, Accenture is recognised worldwide not just for business performance but for inclusion and diversity too.

“Across the globe, one thing is universally true of the people of Accenture: We care deeply about what we do and the impact we have with our clients and with the communities in which we work and live. It is personal to all of us.” – Julie Sweet, Accenture CEO

Role 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 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

• Architect and govern production-grade agentic systems at enterprise scale: multi-agent orchestration across complex environments, RAG pipelines, policy-based routing, memory management, and programme-level lifecycle observability
• Define RAG pipeline standards across engagements: establish chunking and embedding strategies, set quality benchmarks, and ensure metric-backed tradeoff decisions are documented and transferable
• Set multi-LLM integration standards: vendor-agnostic architecture by default, fallback routing and cost governance as standard design practice across providers including OpenAI, Anthropic, Vertex AI, and open-source models
• Own LLMOps at programme scale: eval strategy, prompt governance, observability tooling 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 stakeholders

Basic Qualifications

• Several years of software engineering experience in production environments
• 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
• People lead responsibilities: experience managing, developing, and performance-managing a team of engineers; setting individual development plans and conducting career conversations

What’s In It For You

At Accenture in addition to a competitive basic salary, you will also have an extensive benefits package which includes up to 25 days’ vacation per year, private medical insurance and 3 extra days leave per year for charitable work of your choice.

Flexibility and mobility are required to deliver this role as there will be requirements to spend time onsite with our clients and partners to enable delivery of the outstanding services we are known for