AI Automation Engineer
Tasks
- Architect scalable microservices for LLM RAG agent workflows
- Design and build multi agent workflow automation patterns
- Embed observability for production services
- Ensure secure scalable observable and cost efficient agent and service delivery
- Implement prompt engineering patterns retrieval pipelines and caching
- Lead bug fix security patch and performance tuning sprints
- Lead cross functional engineering to gather requirements and deliver solutions
- Maintain documentation for agents applications and deployment processes
- Manage agile delivery backlog and end to end engineering
- Mentor technical support and troubleshooting for deployed applications
- Own on call runbooks SLOs and incident reviews
- Profile inference latency and optimize GPU CPU utilization
- Write and maintain unit tests and integration tests
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | AgentOps | Agentic AI | Azure | Azure OpenAI | CPQ | CPU Utilization | Caching | Copilot Studio | GPU Utilization | Google Cloud | Incident Management | Integration Testing | LLMOps | Language Models | Large Language Models | Microservices | Observability | Power Automate | Prompt engineering | Python | Retrieval-Augmented Generation | SLO | Salesforce | Salesloft | Service Cloud | Unit Testing | Vector Search
Education
N/A
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