Related skills
microservices apis mlops cloud architecture llm📋 Description
- Lead end-to-end AI and generative AI architecture from use-case to production
- Design cloud-native AI architectures using data, ML, and LLM platforms
- Define reference architectures, patterns, and best practices for enterprise AI
- Evaluate and select AI platforms and models by value, risk, cost
- Partner with business and execs to identify high-value AI opportunities
- Translate business requirements into solution designs and roadmaps
🎯 Requirements
- Bachelor’s or Master’s in CS, Engineering, or related field
- 8+ years in solution architecture or senior tech roles; 4+ in AI/ML
- Strong ML, generative AI, and LLM architectures knowledge
- Experience architecting AI on AWS: SageMaker and Bedrock
- Deep knowledge of cloud architecture, APIs, microservices, and events
- Balance technical depth with business, risk, and regulatory needs
🎁 Benefits
- 4 weeks of vacation from day one
- Flexible working hours
- Modular group insurance plan
- Public transport or parking reimbursement
- Referral bonuses
- Training tailored to your areas of expertise
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