Agentic AI Engineer
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Key skills for this role
Role Overview
Develop advanced agentic systems and intelligent AI solutions.
Design, architect, and build scalable production-grade AI systems.
The source describes the role as an Agentic Engineer or Data Scientist.
Key Skills for This Role
Full Job Posting
About the company
CoffeeBeans Consulting is a software consulting firm delivering engineering, AI, and data science solutions.
The company builds production-grade ML and GenAI systems for fintech, retail, healthcare, logistics, and other sectors.
Role overview
Develop advanced agentic systems and intelligent AI solutions.
Design, architect, and build scalable production-grade AI systems.
The source describes the role as an Agentic Engineer or Data Scientist.
Location and travel
- The role may be based in Bangalore or Hyderabad.
- Candidates based in Bangalore should be willing to travel to Indonesia for six months to one year.
Key responsibilities
- Optimize prompts and write evaluation tests.
- Create custom guardrails for complex domain contexts.
- Use MLflow, LangSmith, or similar tools for debugging.
- Design multi-agent systems and scalable agentic workflows.
- Implement RAG pipelines and work with vector embeddings and databases.
- Build orchestration frameworks and end-to-end AI workflows.
- Collaborate with cross-functional teams and integrate emerging AI tools.
Required skills and qualifications
- Three to six years of experience in data science, machine learning, or AI engineering.
- Strong agent engineering and agent-based architecture experience.
- Hands-on experience with RAG, vector embeddings, semantic search, and multi-agent orchestration.
- Proficiency in Python and relevant ML or AI libraries.
- LangChain and LangGraph experience are mandatory.
- Strong understanding of LLMs, prompt engineering, problem solving, and system design.
Requirements
- Three to six years of experience in data science, machine learning, or AI engineering.
- Strong experience in agent engineering and agent-based architecture.
- Hands-on experience with RAG pipelines, vector embeddings, and semantic search.
- Experience with multi-agent orchestration and workflow design.
- Proficiency in Python and relevant machine learning or artificial intelligence libraries.
- Mandatory experience with LangChain.
- Mandatory experience with LangGraph.
- Solid understanding of large language models and prompt engineering.
- Strong problem-solving and system-design skills.
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