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. **Ideal Candidate Profile** **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. **Please fill the application form** https://airtable.com/appzfqYRRezzTk9ru/pagAcs0li3pdpQRYK/form Job Type: Full\-time 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