AI Software Engineer | Spain

6001 TECNILOGICA ECOS. Company; Madrid; Presencial; EUR 65.000 - 95.000; Jornada completa

Descripción de la vacante

Accenture is seeking an AI Engineer (Agentic/Applied) to design, build, and deploy production-grade agentic AI systems for enterprise clients. You will work directly with client engineering teams, lead design sessions, and create reusable patterns and accelerators that scale across engagements.

You will own RAG pipelines, embeddings, vector search, and context engineering, integrating OpenAI, Anthropic, Vertex AI, and open-source models with robust LLMOps and observability practices.

Formación

• Strong software engineering experience in production environments.
• Hands-on experience deploying agentic AI solutions in production.
• Direct experience calling LLM APIs (OpenAI, Anthropic, Vertex AI) in production code.
• RAG pipeline ownership: embeddings, chunking, vector DBs, context engineering.
• LLMOps fundamentals: eval harness design, prompt versioning, observability.

Responsabilidades

• Design and build production-grade agentic systems end-to-end: multi-agent orchestration, RAG pipelines, policy routing, tool invocation, memory management, observability.
• Build and own RAG pipelines: embeddings, chunking strategy, vector search, context window tuning against quality targets.
• Integrate across LLM providers (OpenAI, Anthropic, Vertex AI) with routing, token, cost, latency management.
• Implement LLMOps in production: eval harnesses with real quality metrics, prompt versioning, observability tooling.
• Collaborate with client engineering teams to design, prototype, and deploy agentic solutions.

Conocimientos

Production-grade software engineering

Agentic AI systems

LLM integration

Production observability

Python/Java

Cloud-native tooling

LLMOps

Herramientas

LangGraph

CrewAI

AutoGen

LangSmith

Kubernetes

Docker

Descripción del empleo

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

• 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

Basic Qualifications

• Strong 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

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. Visitwww.accenture.com

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