AI Agent Engineer

You will work on Agentic AI systems — combining LLMs, tools, workflows, and reasoning to automate real- world business processes in domains like insurance, energy, and enterprise software development (SDLC).
We value attitude, ownership, and learning ability more than years of experience.
This is not a traditional AI/ML role.
We are looking for curious, fast- learning engineers who are passionate about building the next generation of AI agents and intelligent systems.

What You Will Do

Continuously improve agent performance (accuracy, latency, cost)
Design and build AI agents using LLMs (OpenAI, Claude, Llama, Qwen, Falcon, etc.)
Experiment with prompt engineering, tool use, memory systems, and evaluation frameworks
Collaborate with domain experts to translate business problems into AI- driven solutions
Integrate AI agents with APIs, databases, and enterprise systems
Develop multi- step agent workflows (planning → reasoning → tool use → reflection)Build RAG pipelines (embedding, vector DB, retrieval optimization)

Who You Are
Mindset (Very Important)
Strong growth mindset — fast learner, adaptable
Comfortable with uncertainty and rapid change
Willing to experiment, fail, and iterate
High ownership — proactive and self- driven
Curious about how systems work under the hood
Passionate about building real products, not just demos
Required Skills & Background
1–4 years experience in Software Engineering / AI / ML / Data Engineering
Understanding of LLM fundamentals (tokens, context, prompting, limitations)
Familiar with AI agent frameworks (LangChain, LlamaIndex, etc.)
Strong programming in Python (preferred) or TypeScript
Familiar with REST APIs and SQL/NoSQL databases
Basic knowledge of RAG, embeddings, and vector databases
Good at speaking English
Nice to Have
Experience with multi- agent systems
Experience with open- source LLMs (Llama, Qwen, Falcon, DeepSeek)
Experience with fine- tuning (LoRA, PEFT)
Experience with private AI / on- prem deployment
Knowledge of MLOps / LLMOps, Docker, Kubernetes
Exposure to insurance, energy, or finance domains

What You Will Learn

Optimizing cost, latency, and accuracy
Transitioning from AI demos to real- world systems
Designing Agentic AI architectures
Working with private enterprise AI systems
Building production- grade AI agents

Career Growth

Exposure to global clients and enterprise AI projects
Path to Senior Agentic AI Engineer, AI Architect, AI Product Engineer

Why Join Us

Exposure to international markets
Work on real AI systems and business problems
Fast growth and high impact environment
AI- first engineering culture
Build domain- specific AI platforms

Bonus

Strong problem- solving mindset
Actively follow AI trends
Focus on quality and craftsmanship
Side projects (agents, bots, tools)

Cập nhật gần nhất lúc: 2026-04-04 17:00:04