AI Engineer (Applied AI & Backend | LLMs / RAG)
DaCodes
Posted: April 14, 2026
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Quick Summary
AI Engineer with experience in LLMs and RAG, building advanced AI systems for intelligent solutions
Required Skills
Job Description
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
β’ Build and improve AI-powered features using LLMs (e.g. chatbots, copilots, internal tools)
β’ Contribute to the development of RAG pipelines (document ingestion, embeddings, retrieval)
β’ Develop backend services and APIs to support AI applications
β’ Work with vector databases and semantic search systems
β’ Collaborate on designing scalable AI solutions (with guidance from senior team members)
β’ Support deployment and monitoring of AI systems in production environments
β’ Experiment with new AI tools and frameworks to improve development speed and quality
Requirements:
β
What Weβre Looking For (Must-have)
β’ 5+ years of software engineering experience
β’ Strong backend skills (Python and/or TypeScript)
β’ Hands-on experience with LLMs (OpenAI, Anthropic, etc.)
β’ Experience building AI-powered features or applications
β’ Basic understanding of RAG concepts (embeddings, retrieval, vector search)
β’ Experience working with APIs and modern backend architectures
β’ Solid problem-solving skills and willingness to learn
β Nice to Have
β’ Experience with LangChain, LangGraph, or similar frameworks
β’ Exposure to AI agents or multi-step workflows
β’ Experience with vector databases (Pinecone, Weaviate, etc.)
β’ Familiarity with cloud platforms (AWS, Azure, GCP)
β’ Experience deploying applications (Docker, CI/CD)
β’ 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
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