AI Architect (Cloud & Generative AI)
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Job Location:
Monthly Salary:
Posted on:
Yesterday
Vacancies:
1 Vacancy
Job Summary
JOB DESCRIPTION:
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 Youll 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.
The base pay for this position is
N/AIn specific locations the pay range may vary from the range posted.
JOB FAMILY:
Product Development
DIVISION:
ADC Diabetes Care
LOCATION:
Spain > Barcelona : Av. Diagonal 601
ADDITIONAL LOCATIONS:
WORK SHIFT:
Standard
TRAVEL:
No
MEDICAL SURVEILLANCE:
Not Applicable
SIGNIFICANT WORK ACTIVITIES:
Not Applicable
Required Experience:
Staff IC
Key Skills
- APIs
- Pegasystems
- Spring
- SOAP
- .NET
- Hybris
- Solution Architecture
- Service-Oriented Architecture
- Adobe Experience Manager
- J2EE
- Java
- Oracle
About Company
WHO WE ARE CREATING LIFE-CHANGING TECHNOLOGY From removing the regular pain of fingersticks as people manage their diabetes to connecting patients to doctors with real-time information monitoring their hearts, from easing chronic pain and movement disorders to testing half the world’s ... View more
