5-7 years of experience in AI engineering or related fields
Strong background in LLM integration and prompt engineering
Proficiency in building and optimizing RAG pipelines
Experience with vector databases and semantic search
Familiarity with enterprise platforms like Oracle ERP and ServiceNow
Knowledge of AI governance and observability frameworks
Ability to collaborate effectively with cross-functional teams
Responsibilities
Design and develop Agentic AI solutions and multiagent workflows
Build and optimize RAG pipelines for knowledge retrieval
Develop prompts and frameworks to enhance AI response quality
Integrate AI agents with various enterprise platforms and tools
Implement performance monitoring and hallucination mitigation strategies
Collaborate with Product Managers and Data Engineers to enhance agent effectiveness
Benefits
Flexible work arrangements
Opportunities for professional development
Access to cutting-edge AI technologies
Collaborative and innovative work environment
Health and wellness programs
Full Job Description
Role description
The LLM Engineer will be responsible for designing building and optimizing enterprise grade AI agents that power the Clients Store Assistant and Equipment Maintenance solutions.
The role focuses on LLM integration prompt engineering agent orchestration RAG pipelines memory management tool calling and AI governance to enable reliable and scalable Agentic AI capabilities
Key Responsibilities
Design and develop Agentic AI solutions including orchestrator agents intent routers memory components AI skills tool integrations and multiagent workflows.
Build and optimize Retrieval Augmented Generation RAG pipelines using vector databases semantic search knowledge retrieval and enterprise content repositories
Develop prompts reasoning frameworks guardrails and agent instructions to improve response quality task completion accuracy and business relevance.
Integrate AI agents with enterprise platforms including Oracle ERP ServiceNow MCP servers APIs business workflows and operational tools.
Implement AI observability tracing evaluation frameworks hallucination mitigation and performance monitoring for production AI systems
Collaborate with Product Managers Data Engineers Business SMEs and AI Architects to continuously improve agent effectiveness and business outcomes
