AI Architect, Python

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Spyrosoft

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 2016

🤝 B2B

🏢 Enterprise

🤖 Artificial Intelligence

B2B • Enterprise • Artificial Intelligence

Spyrosoft is a European technology services and software engineering company that partners with enterprises to deliver digital transformation, custom software, and IT consulting. It provides cloud, AI/ML, embedded and IoT development, cybersecurity, product design, managed services, and staff augmentation, and builds platforms and products such as DebtPro, Allpro, and VoicePro. Spyrosoft serves clients across multiple sectors including automotive, healthcare and life sciences, financial services, geospatial, media and entertainment, robotics and energy, and operates from offices across Europe, the UK, and the US.

📋 Description

• Design end-to-end AI solution architectures for enterprise environments • Lead the technical design of Generative AI and Machine Learning solutions • Build production-ready AI services using Python • Define AI platform architecture, integration patterns and deployment strategies • Design scalable RAG (Retrieval-Augmented Generation) solutions • Select appropriate LLMs, vector databases and AI frameworks • Collaborate with Software Engineers, Data Engineers, Data Scientists and business stakeholders • Define security, governance and responsible AI best practices • Review solution designs and mentor engineering teams • Drive AI engineering standards and best practices across projects

🎯 Requirements

• 7+ years of software engineering experience • 3+ years of commercial experience delivering AI or Generative AI solutions • Expert-level Python programming skills • Strong experience with LLM-based applications • Experience with frameworks such as LangChain, LangGraph, LlamaIndex or similar • Experience designing RAG architectures • Experience with vector databases (Pinecone, Weaviate, Milvus, Chroma, Azure AI Search or similar) • Experience integrating AI services through APIs • Knowledge of prompt engineering techniques • Experience deploying AI solutions to cloud environments (Azure, AWS or GCP) • Familiarity with containerization (Docker) and Kubernetes • Experience with CI/CD and software architecture best practices • Excellent communication and stakeholder management skills • Fluent English - C1