Agentic AI Lead

Lancesoft APAC; Malaysia; On-site; MYR 200,000 - 320,000; Full time

Job summary

Lancesoft APAC seeks an Agentic AI Lead to design, develop, and deploy intelligent AI agents and multi-agent systems for enterprise workflows. The role emphasizes reasoning, planning, tool usage, and autonomy with governance.

You will lead development of agentic workflows, integrate with enterprise APIs, and implement robust planning, memory, and human-in-the-loop controls. Strong cloud engineering experience is essential.

Qualifications

• Hands-on experience with agentic AI, generative AI, LLM apps, and multi-agent systems.
• Strong software engineering practices: Python, REST APIs, asynchronous programming.
• Proficiency with LangGraph and LangChain; exposure to CrewAI, AutoGen, Semantic Kernel, ADK or similar frameworks.
• Deep understanding of RAG architecture, embeddings, vector databases, retrieval optimization.

Responsibilities

• Design autonomous AI agents and multi-agent systems for enterprise use cases.
• Build agentic workflows using LangGraph, LangChain, CrewAI, AutoGen, Semantic Kernel, ADK.
• Create AI copilots for troubleshooting and incident management.
• Implement planning, reasoning, memory, tool-calling, orchestration, and human-in-the-loop capabilities.
• Design RAG pipelines with embeddings, chunking strategies, vector databases, retrieval tuning.
• Integrate AI agents with enterprise apps, APIs, databases, and cloud services.
• Develop guardrails, fallback strategies, evaluation frameworks, observability, and responsible AI controls.
• Deploy production-grade AI solutions using Docker, CI/CD, Kubernetes, and cloud services.
• Optimize LLM apps for cost, latency, reliability, accuracy, and token usage.
• Collaborate with stakeholders to translate requirements into scalable AI solutions.
• For Lead roles: mentor engineers, define reference architectures, set engineering standards.

Skills

Agentic AI

Generative AI

LLM applications

Multi-agent systems

Tools

LangGraph

LangChain

CrewAI

AutoGen

Semantic Kernel

ADK

Job description

Position Overview

We are seeking a skilled Agentic AI Lead to design, develop, and deploy intelligent AI agents and multi-agent systems that can reason, plan, use tools, and execute complex enterprise workflows with defined autonomy and governance. The role requires strong hands-on experience in Generative AI, LLM applications, RAG architectures, agent orchestration frameworks, cloud AI platforms, and production-grade AI engineering.

• Design and develop autonomous AI agents and multi-agent systems for enterprise use cases.
• Build agentic workflows using frameworks such as LangGraph, LangChain, CrewAI, AutoGen, Semantic Kernel, ADK, or similar technologies.
• Build build AI copilots equivalent agents for troubleshooting and incident management
• Implement planning, reasoning, memory, tool-calling, orchestration, and human-in-the-loop capabilities.
• Design and implement RAG pipelines using embeddings, chunking strategies, vector databases, retrieval tuning, and context optimization.
• Integrate AI agents with enterprise applications, APIs, databases, cloud services, and business workflows.
• Develop guardrails, fallback strategies, evaluation frameworks, observability, and responsible AI controls.
• Deploy production-ready AI solutions using Docker, CI/CD pipelines, Kubernetes, and cloud-native services.
• Optimize LLM applications for cost, latency, reliability, accuracy, and token utilization.
• Collaborate with business stakeholders, architects, product teams, and delivery teams to translate requirements into scalable AI solutions.
• For Lead/Architect roles: mentor engineers, define reference architectures, establish engineering standards, and support solutioning and presales activities.

Mandatory Skills

• Strong hands-on experience in Agentic AI, Generative AI, LLM applications, and multi-agent systems.
• Expertise in Python programming, REST APIs, asynchronous programming, and software engineering best practices.
• Hands-on experience with LangGraph and LangChain; exposure to CrewAI, AutoGen, Semantic Kernel, ADK, or similar frameworks.
• Strong understanding of RAG architecture, embeddings, semantic search, vector databases, and retrieval optimization.