AI Engineer
Tasks
- Build agentic and multi agent workflows
- Build deploy and operate AI workloads on AWS
- Contribute to building AI platforms and reusable components
- Design and build LLM based systems
- Develop prompt engineering and optimization
- Evaluate LLM quality reliability safety and performance
- Implement CI/CD pipelines
- Implement observability with logs metrics traces and alerts
- Implement responsible AI governance and quality standards
- Implement retrieval-augmented generation
- Improve scalability reliability performance security and cost
- Integrate LLMs with REST APIs
- Mentor junior engineers on generative and agentic AI
- Monitor model behavior system health latency and failures
- Own AI solution lifecycle from prototype to production
- Set up automated testing and versioning for AI systems
- Use function calling and tools
Perks/Benefits
- Bike to work
- Career progression
- Educational assistance
- Employee assistance program
- Employee discount
- Enhanced maternity/paternity leave
- Financial advice
- Fitness classes
- Flexible remote working
- Generous holiday allowance
- Gym discounts
- Incentivised certifications
- Life assurance
- Marriage civil partnership leave
- Mentorship coaching
- Mindfulness workshops
- Pension
- Private healthcare
- Quarterly profit share
- Special leave policies
Skills/Tech-stack
AWS Bedrock | Agent systems | Agentic Workflows | Alerting | Amazon SageMaker | Automated testing | CI/CD | Distributed Systems | Embeddings | Function Calling | Generative AI | LLM Evaluation | Logging | Metrics | Monitoring | Multi-Agent | Multi-Agent Systems | Observability | Prompt engineering | Python | REST APIs | Retrieval-Augmented Generation | Tracing | Vector Databases | Vector Search
Education
N/A
Roles
AI | AI Engineer | Engineer
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