Elevation AI is seeking a high-caliber **AI Engineer** with a "Backend-First" mindset. We need a technical architect who understands the **Python Data Model** as deeply as they understand LLM reasoning loops. You’ll be at the forefront of shaping how generative AI is applied in production—building agents that combine reasoning, planning, tool integration, and multi-step orchestration to transform business workflows.This is a technical builder role with significant ownership. You will architect production-ready agents, push the boundaries of what agentic AI can do, and directly influence the evolution of our platform and engineering culture.
**What We Offer**
- Opportunity to build and lead next-generation agent development projects.
- Competitive pay, benefits, and equity potential.
- A startup culture of experimentation, learning, and impact.
- Work with a highly innovative team pushing the boundaries of generative AI.
**How We Work**
- **Excellence in everything**: We set a high bar for code quality, scalability, and reliability.
- **Bias for action**: Progress over perfection, with an embrace of the art of the possible.
- **Innovation mindset**: Stay ahead of the curve on emerging AI methods and frameworks.
- **Transparency & accountability**:Clear ownership, documentation, and follow-through.
- **Collaborative intensity**: Engineering, product, and client teams work in tight cycles.
**Responsibilities**
- **Production-Grade Agent Architecture**: Architect autonomous agents capable of reasoning, planning, and tool execution using frameworks like LangGraph, CrewAI, or custom orchestration.
- **High-Performance Backend**: Develop robust, asynchronous Python services to handle complex multi-step workflows and real-time tool integrations.
- **Engineering Rigor**: Implement comprehensive testing suites (unit, integration, and E2E)



and monitoring to ensure agent reliability in non-deterministic environments.
- **Systems & Data Design**: Design RAG pipelines and vector database integrations with a focus on data structures, retrieval latency, and memory management.
- **Performance Engineering**: Profile, debug, and optimize code for concurrency and scalability, ensuring systems handle production-level loads.
**Experience & Capability**
- Bachelor’s or Master’s in Computer Science, Software Engineering, or Artificial Intelligence.
- 4+ years of professional software engineering with a deep-rooted understanding of Python fundamentals: the data model, OOP principles, decorators, context managers, and memory management.
- A "Test-First" mentality. Experience with pytest, mocking, and performance debugging tools.
- Demonstrated experience deploying AI agents into production using LangChain, LangGraph, or LlamaIndex.
- Solid grounding in distributed systems, API design, and cloud-native architectures (AWS/GCP/Azure).
- Strong practical understanding of LLMs, agent architectures, and production deployment challenges.
- Hands-on with vector databases and RAG pipelines.
- Skilled in prompt engineering, fine-tuning, and LLM APIs (OpenAI, Anthropic, Mistral, LLaMA, etc.).
- Familiarity with MLOps for LLMs (deployment, monitoring, evaluation, feedback loops).
- Solid grounding in system design and distributed architectures.
- Experience with AI coding tools (Cursor, Co-Pilot, etc.).Ways to Stand Out
- Experience with autonomous frameworks (AutoGPT, BabyAGI, CrewAI, or custom).
- Prior work in startups or fast-paced environments with high technical ownership.
- Applied research or projects in multi-agent systems, reflection, or emergent behavior.
- Open-source contributions in the agentic AI ecosystem.
Pay: $95.00 - $110.00 per hour
Expected hours: 40 per week
Application Question(s):
- What is your expected compensation?
**Language**:
- English (required)
Work Location: Remote

📌 Ai Engineer (Guadalajara)
🏢 Elevation AI
📍 Guadalajara