AI Engineer (Applied AI & Backend | LLMs / RAG)

🌍 About the Role

We are looking for an AI Engineer with a strong foundation in backend development and applied AI to join our team.

This role is ideal for someone who has already worked with LLMs, RAG, or AI-powered features, and is looking to grow into building more advanced AI systems such as agent-based architectures and production-grade AI platforms.

You will collaborate with experienced engineers and cross-functional teams to design and build intelligent solutions, while continuing to deepen your expertise in modern AI systems.

🚀 What You’ll Do

• Build and improve AI-powered features using LLMs (e.g. chatbots, copilots, internal tools)
• Contribute to the development of RAG pipelines (document ingestion, embeddings, retrieval)
• Develop backend services and APIs to support AI applications
• Work with vector databases and semantic search systems
• Collaborate on designing scalable AI solutions (with guidance from senior team members)
• Support deployment and monitoring of AI systems in production environments
• Experiment with new AI tools and frameworks to improve development speed and quality

🌍 About the RoleWe are looking for an AI Engineer with a strong foundation in backend development and applied AI to join our team.This role is ideal for someone who has already worked with LLMs, RAG, or AI-powered features, and is looking to grow into ...

✅ What We’re Looking For (Must-have)

• 5+ years of software engineering experience
• Strong backend skills (Python and/or TypeScript)
• Hands-on experience with LLMs (OpenAI, Anthropic, etc.)
• Experience building AI-powered features or applications
• Basic understanding of RAG concepts (embeddings, retrieval, vector search)
• Experience working with APIs and modern backend architectures
• Solid problem-solving skills and willingness to learn

⭐ Nice to Have

• Experience with LangChain, LangGraph, or similar frameworks
• Exposure to AI agents or multi-step workflows
• Experience with vector databases (Pinecone, Weaviate, etc.)
• Familiarity with cloud platforms (AWS, Azure, GCP)
• Experience deploying applications (Docker, CI/CD)
• Interest in prompt engineering or AI evaluation techniques

🧠 What This Role Is (and Is Not)

This role is:

✔ A strong engineering role with exposure to AI systems
✔ A growth path toward advanced AI architectures
✔ A hands-on position building real products

This role is not:

✖ A pure research or data science position
✖ A senior AI architect role (yet)
✖ A prompt-only or no-code AI role

🌍 About the Role

We are looking for an AI Engineer with a strong foundation in backend development and applied AI to join our team.

This role is ideal for someone who has already worked with LLMs, RAG, or AI-powered features, and is looking to grow into building more advanced AI systems such as agent-based architectures and production-grade AI platforms.

You will collaborate with experienced engineers and cross-functional teams to design and build intelligent solutions, while continuing to deepen your expertise in modern AI systems.

🚀 What You’ll Do

• Build and improve AI-powered features using LLMs (e.g. chatbots, copilots, internal tools)
• Contribute to the development of RAG pipelines (document ingestion, embeddings, retrieval)
• Develop backend services and APIs to support AI applications
• Work with vector databases and semantic search systems
• Collaborate on designing scalable AI solutions (with guidance from senior team members)
• Support deployment and monitoring of AI systems in production environments
• Experiment with new AI tools and frameworks to improve development speed and quality

🌍 About the RoleWe are looking for an AI Engineer with a strong foundation in backend development and applied AI to join our team.This role is ideal for someone who has already worked with LLMs, RAG, or AI-powered features, and is looking to grow into ...

✅ What We’re Looking For (Must-have)

• 5+ years of software engineering experience
• Strong backend skills (Python and/or TypeScript)
• Hands-on experience with LLMs (OpenAI, Anthropic, etc.)
• Experience building AI-powered features or applications
• Basic understanding of RAG concepts (embeddings, retrieval, vector search)
• Experience working with APIs and modern backend architectures
• Solid problem-solving skills and willingness to learn

⭐ Nice to Have

• Experience with LangChain, LangGraph, or similar frameworks
• Exposure to AI agents or multi-step workflows
• Experience with vector databases (Pinecone, Weaviate, etc.)
• Familiarity with cloud platforms (AWS, Azure, GCP)
• Experience deploying applications (Docker, CI/CD)
• Interest in prompt engineering or AI evaluation techniques

🧠 What This Role Is (and Is Not)

This role is:

✔ A strong engineering role with exposure to AI systems
✔ A growth path toward advanced AI architectures
✔ A hands-on position building real products

This role is not:

✖ A pure research or data science position
✖ A senior AI architect role (yet)
✖ A prompt-only or no-code AI role