AI Architect Engineer
hace 3 días
Madrid
ph3We are: /h3 pA 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. /p h3You are: /h3 pAn 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. /p pYou’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 /p h3The Work: /h3 pYou’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. /p h3Agent Architecture Engineering /h3 ul lipDesign and build enterprise-ready AI agents incorporating retrieval, orchestration, policy-based routing, tool invocation, evaluation harnesses, and lifecycle observability. /p /li lipImplement resilient, testable, and maintainable agentic workflows that can be iterated on quickly. /p /li /ul h3AI Platform Integration /h3 ul lipDevelop and/or extend abstraction layers across AI providers (Anthropic, Google, OpenAI, etc.) to enable seamless integration and multi-provider enablement. /p /li lipContribute to shared libraries, SDKs, and patterns that can be reused across clients. /p /li /ul h3Cloud-Native Engineering /h3 ul lipLeverage containerization (Kubernetes, Docker), microservices, serverless, event-driven architectures, CI/CD, and observability stacks to deliver scalable AI-native systems. /p /li lipOwn deployment, monitoring, and troubleshooting for your services in production. /p /li /ul h3Domain-Specific Workflows /h3 ul lipTailor and deploy agentic applications across verticals (e.g., finance, healthcare, retail), adapting to domain-specific processes and constraints. /p /li lipWork closely with client SMEs to translate business workflows into agentic solutions. /p /li /ul h3Client Engagement /h3 ul lipParticipate in and/or lead design workshops, POCs, and code-with sessions to shape data-driven agent workflows with stakeholders, fostering trust and adoption. /p /li lipCommunicate trade-offs, risks, and recommendations clearly to both technical and non-technical audiences. /p /li /ul h3Measure Improve /h3 ul lipDefine and use key metrics, test harnesses, and evaluation plans to measure agent accuracy, latency, safety, and cost effectiveness. /p /li lipIterate rapidly based on data, feedback, and changing requirements. /p /li /ul h3Knowledge Sharing /h3 ul lipCraft reusable patterns, documentation, and best practices that influence internal assets and client roadmaps. /p /li lipContribute to internal communities of practice around AI-native and agentic engineering. /p /li /ul pTravel may be required for this role. The amount of travel will vary from 25% to 75% depending on business need and client requirements. /p h3Job Qualifications /h3 h3Key Responsibilities /h3 ul lipArchitect 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 /p /li lipDefine RAG pipeline standards across engagements: establish chunking and embedding strategies, set quality benchmarks, and ensure metric-backed tradeoff decisions are documented and transferable /p /li lipSet 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 /p /li lipOwn LLMOps at programme scale: eval strategy, prompt governance, observability tooling standards, safety monitoring and cost controls across multiple concurrent systems /p /li lipLead 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 /p /li lipShape and publish reusable patterns, accelerators, and engineering standards that scale across the practice and reduce ramp-up time on new client engagements /p /li lipOwn 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 /p /li /ul h3Basic Qualifications /h3 ul lipStrong software engineering experience in production environments /p /li lipHands‑on experience designing and deploying agentic AI solutions in a production environment — non‑negotiable /p /li lipDemonstrated experience with agentic orchestration frameworks: LangGraph, CrewAI, AutoGen, or equivalent — at production depth, not tutorial level /p /li lipDirect experience calling LLM APIs (OpenAI, Anthropic, Vertex AI) in production code: provider abstraction, token management, latency and cost tradeoffs /p /li lipRAG pipeline ownership: embeddings, chunking strategy, vector databases, and context engineering /p /li lipLLMOps fundamentals: eval harness design, prompt versioning, and production observability /p /li lipCloud‑native engineering maturity: Kubernetes, Docker, microservices, serverless, CI/CD, and IaC (Terraform or Helm) /p /li lipStrong Python; Java or equivalent backend language acceptable; production debugging and observability experience /p /li lipQuality 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 /p /li lipPeople lead responsibilities: experience managing, developing, and performance‑managing a team of engineers; setting individual development plans and conducting career conversations /p /li /ul h3About Accenture /h3 pAccenture 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. /p pVisit us at /p h3Declaración de igualdad de oportunidades en el empleo /h3 pCreemos 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 nuestro clientes y comunidades. /p /p #J-18808-Ljbffr