Lavu Tech Solutions
AI Agentic Solutions Engineer
- Compensation
- Not disclosed
- Location
- Bayan Lepas, Penang
- Work setup
- Onsite
- Seniority
- Not specified
- Employment
- Contract
- Experience
- Not specified
- Category
- Solutions engineering
- Posted
Skills
Nice to have
- 1) Experience implementing MCP-based tool integrations.
- 2) Knowledge of ReAct, Reflection, and advanced agent reasoning frameworks.
- 3) Experience building automated reporting systems.
- 4) Hands-on experience with Plotly or Vega-Lite.
- 5) Frontend development experience with React, Next.js, or Streamlit.
- 6) Experience with cloud platforms such as Azure, AWS, or GCP.
- 7) Knowledge of AI governance, observability, and model evaluation.
- We are seeking an experienced AI Agentic Solutions Engineer to design, develop, and deploy enterprise-grade Generative AI solutions leveraging Large Language Models (LLMs), multi-agent orchestration f
Full description
AI Agentic Solutions Engineer / LLM Orchestration Developer
This is for Chatbot project
- Strong Python development experience.
- Hands-on experience with at least one (LangGraph, CrewAI, AutoGen, Semantic Kernel)
- Experience building RESTful APIs and integrating third-party services.
- Experience developing scalable backend applications using FastAPI or Flask.
- Strong understanding of LLM-based architectures and prompt engineering.
- Experience with asynchronous programming, SSE, WebSockets, and job queue
architectures.
Preferred Skills
- Experience implementing MCP-based tool integrations.
- Knowledge of ReAct, Reflection, and advanced agent reasoning frameworks.
- Experience building automated reporting systems.
- Hands-on experience with Plotly or Vega-Lite.
- Frontend development experience with React, Next.js, or Streamlit.
- Experience with cloud platforms such as Azure, AWS, or GCP.
- Knowledge of AI governance, observability, and model evaluation.
We are seeking an experienced AI Agentic Solutions Engineer to design, develop, and deploy enterprise-grade Generative AI solutions leveraging Large Language Models (LLMs), multi-agent orchestration frameworks, and modern backend technologies. The candidate will be responsible for building intelligent agent ecosystems, integrating external tools and services, delivering automated insights and reports, and creating human-in-the-loop workflows that support business-critical use cases.