Senior AI Architect (w/m/x)
Tasks
- Build LLM-based applications
- Build Retrieval-Augmented Generation solutions
- Build agentic and multi agent systems
- Define AI and GenAI end to end architecture
- Define MLOps deployment monitoring and lifecycle management
- Define technical standards and governance
- Design multimodal AI solutions
- Design scalable secure AI architectures
- Drive AI engineering best practices
- Ensure reliable governed explainable AI where needed
- Evaluate emerging AI technologies for business relevance
- Identify AI opportunities and high value use cases
- Industrialize AI use cases into enterprise products
- Lead AI delivery lifecycle from discovery to production support
- Mentor teams in AI architecture and MLOps
- Present solution proposals to stakeholders
- Provide technical leadership to cross-functional teams
- Review designs and deployment strategies for quality
- Translate business requirements into solution designs
Perks/Benefits
- Continuous learning
- Flexible work schedule
- Hybrid work model
- Mentoring
- Relocation assistance not provided
Skills/Tech-stack
API Integration | Agent systems | Agentic Workflows | Cloud Architecture | Cybersecurity | Data Pipelines | Generative AI | LLM orchestration | Language Models | Language Processing | Large Language Models | Lifecycle Management | MLOps | Machine Learning | Model Deployment | Model Monitoring | Modularity | Multi-Agent | Multi-Agent Systems | Multimodal AI | Natural Language | Natural Language Processing | Observability | Prompt engineering | Resilience | Retrieval-Augmented Generation | Scalability | Security | Solution architecture | Versioning
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
AI | AI Architect | Architect | Engineer | Learning Engineer | Machine Learning Engineer
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