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Accenture

Advises businesses and runs their technology

AI Manager

AI Application EngineeringConfirmed live in the last 24 hours
Full-timeMadrid, SpainNo salary listedIn-person

About the Job

Requirements

  • Strong experience in software engineering in production environments.
  • Hands-on experience designing and deploying agentic AI solutions in production.
  • Demonstrated production-depth experience with agentic orchestration frameworks such as LangGraph, CrewAI, AutoGen, or equivalent.
  • Direct experience calling large language model APIs, including OpenAI, Anthropic, or Vertex AI, in production code, including provider abstraction, token management, and latency and cost tradeoffs.
  • Experience owning retrieval-augmented generation pipelines, including embeddings, chunking strategy, vector databases, and context engineering.
  • Knowledge of large language model operations fundamentals, including evaluation harness design, prompt versioning, and production observability.
  • Cloud-native engineering experience with Kubernetes, Docker, microservices, serverless, continuous integration and continuous delivery, and infrastructure as code such as Terraform or Helm.
  • Strong Python skills; Java or an equivalent backend language is acceptable. Production debugging and observability experience is required.
  • Experience managing, developing, and performance-managing a team of engineers, setting individual development plans, and conducting career conversations.

Responsibilities

  • Architect and govern production-grade agentic systems at enterprise scale, including multi-agent orchestration across complex environments, retrieval-augmented generation pipelines, policy-based routing, memory management, and programme-level lifecycle observability.
  • Define retrieval-augmented generation pipeline standards across engagements, including chunking and embedding strategies, quality benchmarks, and documented, transferable metric-backed tradeoff decisions.
  • Set multi-large language model integration standards, using vendor-agnostic architecture by default and making fallback routing and cost governance standard design practices across providers including OpenAI, Anthropic, Vertex AI, and open-source models.
  • Own large language model operations at programme scale, including evaluation strategy, prompt governance, observability tooling standards, safety monitoring, and cost controls across multiple concurrent systems.
  • Lead client engineering engagements at senior level by facilitating architecture design sessions, leading proof-of-concept delivery, and driving 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 by defining accuracy, latency, safety, and cost metrics, and presenting programme-level AI impact in business terms to senior client stakeholders.

Desired Qualifications

  • 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 the Company

Accenture

Advises businesses and runs their technology

Accenture advises large businesses and public agencies on strategy, builds their technology systems and runs ongoing operations. Its teams connect business planning with implementation, covering areas such as cloud migration, cybersecurity and customer experience. Consultants work with clients to redesign processes, while engineers integrate software from technology partners and maintain the resulting systems for multinational organizations. Clients pay for project work or continuing services, including application support and business processes such as finance and customer service. Accenture was founded in 1989 and has its headquarters in Dublin, Ireland.

Company size
10,001+
Company stage
IPO
Headquarters
Dublin, Ireland
Founded
1989

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