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Coding the world of tomorrow
AI Engineer (Applied AI & Backend | LLMs / RAG)
Location
Chile
Posted
91 days ago
Salary
0
Seniority
Mid Level
Job Description
AI Engineer (Applied AI & Backend | LLMs / RAG)
DaCodes.
π 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. π What Youβll 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
Job Requirements
- β What Weβre 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
- β 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
- π§ What This Role Is (and Is Not)
- This role is:
- β A strong engineering role with exposure to AI systems
- β A growth path toward advanced AI architectures
- β A hands-on position building real products
- This role is not:
- β A pure research or data science position
- β A senior AI architect role (yet)
- β A prompt-only or no-code AI role
Benefits
- π Integration with global brands and disruptive startups.
- π‘ Remote work / Home office.
- π If a hybrid or on-site modality is required, you will be informed from the first session.
- β³ Schedule aligned with your assigned project/team.
- π Monday to Friday work schedule.
- π Day off on your birthday.
- π₯ Major medical insurance (applies to Mexico).
- π‘οΈ Life insurance (applies to Mexico).
- π Multicultural teams.
- π Access to courses and certifications.
- π’ Meetups with special guests from the IT industry.
- π‘ Virtual integration events and interest groups.
- π’ English classes.
- π Opportunities within our different business lines.
- π Proudly certified as a Great Place to Work.
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π 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. π What Youβll 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
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