Machine Learning Engineer III - AI Agent Engineer - Digital and Technology Partners - Onsite/Hybrid
Tasks
- Architect end to end agentic AI solutions
- Build and deploy RAG pipelines
- Conduct root cause analysis for agent failures
- Create project documentation
- Design and develop AI agent ecosystems
- Develop agent frameworks with tool usage
- Develop project work plans and milestones
- Establish machine learning development best practices
- Implement LLM based multi agent systems
- Integrate AI solutions with enterprise systems
- Lead technical mentorship and code reviews
- Manage project progress reporting
- Mentor team on statistical analysis methods and tools
- Monitor deployed models' performance
- Orchestrate agent workflows
- Perform hallucination and model drift analysis
- Update models to maintain reliability
Perks/Benefits
- N/A
Skills/Tech-stack
AI Foundry | AI Search | AWS | Agent Orchestration | Agent systems | Anthropic | Apache Spark | Autogen | Azure | Azure AI | Azure AI Foundry | Azure AI Search | Azure DevOps | Azure OpenAI | Chroma | Continuous Delivery | Continuous integration | CrewAI | Deep learning | Elasticsearch | Generative AI | Git | Google Cloud | Jenkins | Langchain | Langgraph | Language Models | Large Language Models | Machine Learning | Model Monitoring | Multi-Agent | Multi-Agent Systems | NoSQL | OpenAI API | Orchestration frameworks | Pinecone | RAG | Retrieval-Augmented Generation | SDLC | SQL | Semantic Kernel | Terraform | Unix | Vector Databases | Weaviate
Education
Bachelor of Arts | Bachelor of Engineering | Bachelor of Science
Roles
AI | AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer | Software Engineer
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