AI Summary
Design, implement, and scale complex generative AI applications. Implement and optimize RAG architectures and deployment strategies for autonomous AI agents. Evaluate agent-based systems and ensure robustness and accuracy.
Key Highlights
Generative AI expertise
RAG architecture implementation
Autonomous AI agent deployment
Key Responsibilities
Design, implement, and scale complex generative AI applications
Implement and optimize RAG architectures
Design deployment strategies for autonomous AI agents
Evaluate agent-based systems
Ensure robustness and accuracy
Technical Skills Required
Benefits & Perks
Relocation to Spain
4 years of experience
Job Description
SR AI ENGINEER - FOCUS GENAI
4 years of experience
Relocation to Spain
Advanced English
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- Proven experience as an AI engineer, data scientist, or AI solutions architect, with a strong focus on generative AI.
- Experience in the design, implementation, scaling, and management of complex generative AI applications, specifically.
- Implementation and optimization of RAG architectures (vector databases, embedding models, indexing).
- Designing deployment strategies for autonomous AI agents and multi-LLM workflows.
- Evaluating agent-based systems: success metrics, response accuracy, robustness, etc.
- Experience using Azure/AWS services such as Azure Foundry, Amazon Bedrock, Vector Engine, or similar tools (LangChain, CrewAI).
- Extensive cloud experience with Azure and/or AWS (IAM, networking, storage, computing, monitoring, security, cost management).
- Proficiency in Python; API integration, event/queue patterns, testing, code review, and documentation.
- Expertise in AI products: defining KPIs, assessing impact, and communicating clearly with non-technical stakeholders.
- Experience with deep learning frameworks (PyTorch, TensorFlow).
- MLOps/LLMOps in production: CI/CD processes, containerization (Docker/K8s), experiment tracking, monitoring of response quality/justification, latency, and cost.
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Modality: Relocation to Spain
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