Senior AI Platform Engineer
Tasks
- Apply prompt engineering model evaluation guardrails responsible AI
- Build AI agents
- Build AI platform capabilities
- Create reusable AI services APIs SDKs
- Define AI use cases technical requirements delivery roadmaps
- Design scalable AI solutions
- Develop RAG pipelines
- Ensure security scalability resilience compliance cost efficiency
- Implement AI observability evaluation monitoring
- Implement MLOps and AI Ops practices
- Integrate LLM providers
- Mentor engineers
Perks/Benefits
- Career coaching
- Certifications support
- Coaching
- Employee assistance programme
- Flexible working hours
- Hybrid work
- Learning opportunities
- Training
- Wellbeing programme
- Workshops conferences
Skills/Tech-stack
AI Ops | APIs | AWS | Anthropic API | Azure | Azure OpenAI | CI/CD | Cloud Native | Cloud-native Architectures | Distributed Systems | Docker | Event Driven | Event-driven architecture | GCP | Guardrails | Infrastructure as Code | Kubernetes | Langchain | Langgraph | MLOps | Microservices | Model Evaluation | Observability | OpenAI API | Prompt engineering | Python | Retrieval-Augmented Generation | Semantic Kernel | Vector Databases | Vector Search | “as-code”
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Regions
Countries
States
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