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AI Native Software Engineer

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Accenture Greece logo

AI Native Software Engineer

Accenture Greece

Location

Madrid, Castellana 85 • Madrid, Parque Empresarial Pta del Este • Madrid, Torre Chamartin • Madrid

Experience

Senior

Posted

Jul 10, 2026

Apply by

August 9, 2026

Applicants

0

Early applicantFull-timeWork from Office

Sign in to apply on web or download the app for more options.

Job Description

**We are:** A forward-thinking services company at the forefront of AI-native innovation. We partner with enterprise clients to create next-generation, agent-powered workflows engineered to scale in real-world settings. Our engineers embed deeply with customers, moving projects beyond experimentation into operational reality. **You are** An AI Native Engineer with a strong foundation in building cloud-native solutions and hands-on experience designing and deploying agentic systems, especially for enterprise environments. You’re a critical thinker who thrives in ambiguity, delivering concrete results by designing, building, and running AI agents that augment workflows and scale across modern infrastructure. You'll shape how enterprises adopt AI-native engineering - either by leading complex agentic solutions and developing engineering talent, or by owning critical technical areas end-to-end as a senior IC **The Work** You’ll partner directly with client stakeholders — acting as both technologist and trusted advisor. You’ll partner with stakeholders to define use cases, rapidly prototype, and deploy agentic workflows that are robust, secure, and operational in complex enterprise domains. Often, these will be net-new platforms and systems that need to be stitched together in our clients’ environments alongside our ecosystem partners. **Agent Architecture & Engineering** - Design and build enterprise-ready AI agents incorporating retrieval, orchestration, policy-based routing, tool invocation, evaluation harnesses, and lifecycle observability. - Implement resilient, testable, and maintainable agentic workflows that can be iterated on quickly. **AI Platform Integration** - Develop and/or extend abstraction layers across AI providers (Anthropic, Google, OpenAI, etc.) to enable seamless integration and multi-provider enablement. - Contribute to shared libraries, SDKs, and patterns that can be reused across clients. **Cloud-Native Engineering** - Leverage containerization (Kubernetes, Docker), microservices, serverless, event-driven architectures, CI/CD, and observability stacks to deliver scalable AI-native systems. - Own deployment, monitoring, and troubleshooting for your services in production. **Domain-Specific Workflows** - Tailor and deploy agentic applications across verticals (e.g., finance, healthcare, retail), adapting to domain-specific processes and constraints. - Work closely with client SMEs to translate business workflows into agentic solutions. **Client Engagement** - Participate in and/or lead design workshops, POCs, and code-with sessions to shape data-driven agent workflows with stakeholders, fostering trust and adoption. - Communicate trade-offs, risks, and recommendations clearly to both technical and non-technical audiences. **Measure & Improve** - Define and use key metrics, test harnesses, and evaluation plans to measure agent accuracy, latency, safety, and cost effectiveness. - Iterate rapidly based on data, feedback, and changing requirements. **Knowledge Sharing** - Craft reusable patterns, documentation, and best practices that influence internal assets and client roadmaps. - Contribute to internal communities of practice around AI-native and agentic engineering. Travel may be required for this role. The amount of travel will vary from 25% to 75% depending on business need and client requirements. ## 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 - Hands on experience in software engineering experience in production environments - Exposure / 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](http://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, ciudadanía 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.

Key Responsibilities

  • Design and build production-grade agentic systems including multi-agent orchestration, RAG pipelines, and policy-based routing.
  • Build and own RAG pipelines involving embeddings, chunking strategies, vector search, and context engineering.
  • Integrate and abstract across multiple LLM providers such as OpenAI, Anthropic, and Vertex AI.
  • Implement LLMOps in production including eval harnesses, prompt versioning, and observability tooling.
  • Embed with client engineering teams to design, prototype, and deploy agentic solutions.
  • Build reusable patterns, accelerators, and playbooks to scale beyond individual client engagements.
  • Define and use metrics to measure agent accuracy, latency, safety, and cost-effectiveness.

Skills Required

PythonJavaKubernetesDockerMicroservicesServerlessCI/CDTerraformHelmLangGraphCrewAIAutoGenOpenAI APIAnthropic APIVertex AIRAGVector DatabasesLLMOpsLangSmithBraintrustCritical thinkingCommunicationProblem solvingAdaptability

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Job Overview

Salary

—

Job Type

Full-time

Experience

Senior

Location

Madrid, Castellana 85 • Madrid, Parque Empresarial Pta del Este • Madrid, Torre Chamartin • Madrid

Application Deadline

August 9, 2026

Total Applicants

0

About Accenture Greece

Accenture Greece logo

Accenture Greece is a leading company in the Technology sector, known for innovation and employee-centric culture.

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