Senior AI/ML Engineer (GenAI, AWS)
Tasks
- Build and optimize RAG systems
- Build evaluation harness
- Build production GenAI systems
- Conduct model evaluation and improve failure modes
- Deploy AI systems to AWS
- Implement LLMOps and AgentOps
- Integrate AI components into backend services and RESTful APIs
- Mentor AI engineers and conduct code reviews
- Provide documentation runbooks and handover
- Write production code across stack
Perks/Benefits
- Access to premium subscriptions
- Conference attendance
- Equipment provided
- Internal training programs
- Paid public holidays
- Paid sick leave
- Paid vacation
- Private medical insurance
- Remote-friendly culture
Skills/Tech-stack
AWS Bedrock | AWS Lambda | AgentOps | Agentic Orchestration | Amazon ECR | Amazon ECS | Amazon S3 | Amazon SQS | Anthropic API | CI/CD | Caching | Containers | Cost Optimization | Drift Detection | Evaluation Harness | Graph orchestration | Infrastructure as Code | Kubernetes | LLMOps | Latency optimization | Model Monitoring | OpenAI API | Prompt management | Python | RAG | Regression testing | State management | Tool use | TypeScript | Version Management | “as-code”
Education
N/A
Roles
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