Senior Artificial Intelligence/Machine Learning Engineer
Tasks
- Automate Kubernetes and container and serverless environments
- Build automated platform services for AI and analytics lifecycle
- Collaborate on governance and compliance requirements
- Conduct design reviews and code reviews and establish best practices
- Design and implement self service automation for onboarding and provisioning
- Design enterprise CI CD pipelines and release management
- Develop infrastructure as code solutions
- Drive operational excellence with monitoring and automated remediation
- Implement agentic AI workflow automation and event driven architectures
- Lead platform automation initiatives for enterprise GenAI and analytics
- Provide technical leadership and mentorship
- Support strategic AI platform adoption initiatives
Perks/Benefits
- Company-paid certifications
- Conference attendance
- Healthcare
- Internal mobility
- Language courses
- Life insurance
- Long-term disability
- Short-term disability
- Udemy access
- Workshops
Skills/Tech-stack
API Integration | Agentic AI | Alerting | Artificial Intelligence | Automated testing | CI/CD | Containers | Continuous Delivery | Continuous integration | Data Governance | Data Lineage | Data Quality | DevOps | DevSecOps | Distributed Computing | Event Streaming | Generative AI | Infrastructure as Code | Kafka | Kubernetes | Language Models | Large Language Models | Logging | MCP | Machine Learning | Metadata Management | Microservices | Monitoring | Networking | Observability | Python | RAG | Release Management | Reliability Engineering | Resilience | Scalability | Security | Serverless | Terraform | Testing Frameworks | Tracing | YARN | “as-code”
Education
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