Ai Architect (Cloud & Generative Ai)
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Job description
Experteer Overview As an AI Architect on Abbott's Diabetes Care platform, you design and deliver cloud-based GenAI solutions that scale from PoC to production.You blend cloud architecture with practical GenAI engineering to build secure, reliable, and cost-efficient systems.You'll shape the GenAI tech stack, ensure safe operation, and drive measurable business outcomes.You work across teams to translate requirements into safe-by-design implementations, delivering high-impact AI features.This is an AI-first role focused on practical delivery at scale.Compensaciones / Beneficios- Own end-to-end GenAI solution architecture including data ingestion, retrieval, context assembly, model/agent logic, evaluation, deployment, and monitoring- Design, build, and optimize RAG systems with grounding and citation patterns- Lead context engineering: prompts, memory/state patterns, tool calls, defenses against prompt injection and data leakage- Build scalable services/APIs (FastAPI/Flask) and connect GenAI to tools and enterprise systems- Define cloud platform patterns for GenAI workloads with DevOps and IaC practices- Add observability for GenAI services: tracing, logs, metrics, dashboards, alerting- Implement evaluation-driven development with golden datasets and automated checks- Establish LLMOps/GenAIOps: versioning, CI/CD, monitoring, incident response- Partner with security, legal, compliance, quality, and product stakeholders; mentor engineers and set standardsResponsabilidades- Strong cloud architecture experience (AWS/Azure/GCP) including security, networking, IAM, and scalable service design- Hands-on GenAI/LLM experience 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 and ability to ship prototypes quickly- Experience building production APIs/services and integrating with enterprise systems- DevOps/CI-CD experience (GitHub Actions and/or Bitbucket pipelines) with automated testing and quality gates- Experience using coding models to accelerate delivery while maintaining code quality, security, and traceability- Strong understanding of GenAI reliability and safety (hallucination mitigation, prompt injection awareness)- Excellent communication and documentation skills for technical and non-technical audiencesRequisitos principales-
Requirements
Proven experience implementing RAG systems, vector stores, and context engineering for reliable grounding
- Strong Python engineering and ability to ship prototypes quickly
- Experience building production APIs/services and integrating with enterprise systems
- DevOps/CI-CD experience (GitHub Actions and/or Bitbucket pipelines) with automated testing and quality gates
- Experience using coding models to accelerate delivery while maintaining code quality, security, and traceability
- Strong understanding of GenAI reliability and safety (hallucination mitigation, prompt injection awareness)
- Excellent communication and documentation skills for technical and non-technical audiencesRequisitos principales