Senior AI Platform Engineer
Tasks
- Apply prompt engineering evaluation and guardrails for responsible AI
- Build and maintain AI platform capabilities
- Collaborate on AI use cases technical requirements and delivery roadmaps
- Create reusable AI services APIs SDKs and platform components
- Design and deploy scalable AI solutions
- Develop and deploy AI agents
- Develop and optimize RAG pipelines
- Ensure security scalability resilience compliance and cost efficiency
- Implement MLOps and AI Ops with CI CD and model lifecycle management
- Implement observability evaluation and monitoring for AI systems
- Integrate and orchestrate LLM providers and AI services
- Mentor engineers and support technical growth
Perks/Benefits
- Career coaching
- Employee assistance programme
- Flexible working hours
- Hybrid work
- Training
- Wellbeing programme
- Workshops and conferences
Skills/Tech-stack
API Development | AWS | Artificial Intelligence | Azure | CI/CD | Compliance | Distributed Systems | Docker | Event Driven | Event-driven architecture | GCP | Infrastructure as Code | Kubernetes | Langchain | Langgraph | Language Models | Large Language Models | MLOps | Machine Learning | Microservices | Model Evaluation | Observability | Prompt engineering | Python | Retrieval-Augmented Generation | Security | 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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