Ai Engineer

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