AI Architect (Cloud & Generative AI)
Abbott Laboratories —Barcelona, Barcelona provincia
- Jornada completa
- Azure
- DevOps
- Máster
Senior Data Architect
Allianz —Barcelona, Barcelona provincia
- Jornada completa
- Trabajo híbrido
- Azure
- DevOps
- Plan de pensiones
Senior Director - Enterprise AI Platforms
AstraZeneca —Barcelona, Barcelona provincia
- Jornada completa
- Microsoft Excel
- Azure
- Informática
Lead Software Developer (Java, Python & AI Systems)
SITA Switzerland Sarl —Barcelona, Barcelona provincia
- Jornada completa
- Azure
- DevOps
- Oficina
- Teletrabajo opcional
Senior Full Stack Developer
Allianz —Barcelona, Barcelona provincia
- Jornada completa
- Trabajo híbrido
- DevOps
- Java
- Máster
- Plan de pensiones

Related jobs to explore

Based on your search for devops security engineer

Senior Staff Security Engineer - Network Security
Nscale —Amer, Girona provincia
By establishing clear trust boundaries, segmentation patterns, and practical standards, you’ll enable the business to move quickly while reducing the risk of…
Senior Cloud Security Engineer
Cint —Barcelona, Barcelona provincia
Provide point of expertise on application, data and network security to our wider engineering teams - engaging with them in order to ensure consistent adoption…
Solicitud rápida

Quiero recibir la alerta de empleo más reciente de devops security engineer en catalunya

Al iniciar sesión en tu cuenta, aceptas las Condiciones del servicio de SimplyHired, nuestra Política sobre cookies y nuestra Política de privacidad.

AI Architect (Cloud & Generative AI)

Abbott Laboratories -
Barcelona, Barcelona provincia

Solicitar ahora

Detalles del empleo

Jornada completa

Cualificaciones

CI/CD
SSO
Azure
Arquitectura Cloud
Derecho
Desarollador iOS
DevOps
iOS
Android
Máster
AWS
Respuesta a incidencias
PostgreSQL
Redis
GitHub
APIs
Escalabilidad
Cloud
Inteligencia artificial
Python
Debugging

Descripción completa del empleo

Role Summary

We are hiring a hands-on AI Architect to design and deliver cloud-based Generative AI solutions across Diabetes Care products and internal enterprise workflows. This role blends modern cloud architecture with practical GenAI engineering: you will define reference architectures, build working prototypes, and guide teams to production with secure, scalable, and cost-efficient patterns.

You will drive GenAI productization: move prototypes from PoC to production with clear quality gates, scalability, security, cost controls, and measurable business outcomes.

You will help define and evolve the GenAI tech stack, including Retrieval-Augmented Generation (RAG), context engineering, and vector stores, to ensure reliable grounding and safe operation.

This role is AI-first: you are expected to use AI tools in your daily work to accelerate delivery while maintaining engineering rigor, traceability, and quality.

What You'll Do

Own end-to-end GenAI solution architecture: data ingestion, retrieval, context assembly, model/agent logic, evaluation, deployment, and monitoring.
Design, build, and optimize RAG systems (chunking/indexing, embeddings, vector stores, hybrid retrieval, re-ranking) with strong grounding and citation patterns.
Lead context engineering: prompt templates, structured outputs, tool/function calling, memory/state patterns for agents, and defenses against prompt injection and data leakage.
Build scalable services and APIs (e.g., FastAPI/Flask) and integrate MCP servers to connect GenAI to tools, data, and enterprise systems.
Define cloud platform patterns for GenAI workloads (networking, IAM, secrets, observability, resiliency) using modern DevOps and Infrastructure-as-Code.
Add observability for GenAI services: distributed tracing, structured logs, metrics (latency, cost, quality), dashboards, and alerting.
Implement evaluation-driven development: golden datasets, automated checks, prompt/agent regression tests, and human review where appropriate.
Establish LLMOps/GenAIOps practices: versioning (prompts/configs/models), CI/CD, monitoring (latency, cost, quality), and incident response for AI services.
Partner with security, legal, compliance, quality, and product stakeholders to translate requirements into safe-by-design solutions; mentor engineers and set standards.

Required Qualifications

Strong cloud architecture experience (AWS/Azure/GCP), including security, networking, IAM, and scalable service design.
Hands-on GenAI/LLM experience delivering solutions beyond notebooks (OpenAI/Azure OpenAI, AWS Bedrock, or similar).
Proven experience implementing RAG systems, vector stores, and context engineering for reliable grounding.
Strong Python engineering (clean code, debugging, testing discipline) and ability to ship prototypes quickly.
Experience building production APIs/services and integrating with enterprise systems.
DevOps and CI/CD experience (GitHub Actions and/or Bitbucket pipelines), including automated testing and quality gates.
Comfortable using coding models to accelerate delivery (e.g., OpenAI Codex, Claude Code, or similar), while maintaining code quality, security, and traceability.
Strong understanding of GenAI reliability and safety (hallucination mitigation, uncertainty handling, secure model usage, prompt injection awareness).
Excellent communication and documentation skills for technical and non-technical audiences.

Preferred Qualifications

Experience with agentic systems (routing, orchestration, multi-step plans, workflow/state management) and common frameworks or equivalent internal tooling.
Experience with vector databases/search platforms (OpenSearch, pgvector/Postgres, Pinecone, Weaviate, Redis) and hybrid retrieval patterns.
Experience deploying cloud solutions that integrate with mobile applications and device ecosystems (iOS/Android) and/or enterprise identity (SSO).
Experience building/operating ML/AI platforms (feature pipelines, training/inference services, MLflow, SageMaker/Vertex/Databricks) and knowing when fine-tuning is appropriate.
Experience working in regulated environments (PII/PHI controls, auditability, traceability) and scaling solutions across multiple products.

Success looks like:

Reusable reference architectures and templates for GenAI services adopted across teams.
Validated prototypes transitioned to production with clear go/no-go criteria and measurable quality.
Improved reliability, safety, and cost-efficiency of GenAI features across products and internal workflows.

Solicitar ahora

Refina tu búsqueda

devops security engineer empleos en catalunya

AI Architect (Cloud & Generative AI)

Senior Data Architect

Senior Director - Enterprise AI Platforms

Lead Software Developer (Java, Python & AI Systems)

Senior Full Stack Developer

Related jobs to explore

Quiero recibir la alerta de empleo más reciente de devops security engineer en catalunya

Related Searches

Role Summary

What You'll Do

Required Qualifications

Preferred Qualifications

Herramientas para candidatos

Herramientas para empresas

Buscar

Mantener la conexión