Stop waiting for the perfect moment. The future of AI is here, and it's agentic. At Maxmodus, we're not just tweaking LLMs – we're building truly intelligent systems that think, plan, adapt, and evolve to revolutionize how small and mid-size businesses (SMBs) operate. We're talking about a paradigm shift, empowering SMBs to achieve operational excellence beyond what even large enterprises can manage today.
We're assembling an elite founding strike team to bring this vision to life. If you're driven by the challenge of building something truly groundbreaking, this is your chance.
The Lead Full-Stack Developer, Agentic AI/LLM, will be a hands-on technical leader responsible for designing, developing, and deploying the core agentic AI functionalities and Large Language Model (LLL) integrations.
AI/LLM Architecture & Strategy
- Lead design and implementation of agentic AI architecture, including multi-agent systems and memory management.
- Select and integrate LLMs (e.g., OpenAI, Claude, open-source).
- Develop strategies for prompt engineering, context window control, and hallucination/bias mitigation.
Core Agentic Development
- Design agent interactions with tools, APIs, and human users.
- Implement planning, memory, and reasoning capabilities for agents.
- Develop API endpoints for AI agents.
Technical Leadership & Mentorship
- Mentor developers and enforce coding/testing best practices.
- Collaborate with product to define AI roadmap.
Full-Stack Contributions (Back-End Focus)
- Develop scalable services in Python or Node.js.
- Manage AI-related data with PostgreSQL, Redis, or MongoDB.
- Ensure secure service communication and access control.
DevOps & Deployment (AI-Specific)
- Deploy AI agents using containerized models or APIs.
- Implement logging and monitoring for agent behavior.
Research & Innovation
- Stay current with AI/LLM/agentic system trends.
- Evaluate and integrate cutting-edge approaches.
Required Skills & Experience
- 7+ years of software development, 3–4+ in AI/LLM.
- Proficiency in Python, Node.js, or Go.
- Hands-on LLM experience including prompt engineering.
- Experience with LangChain, LlamaIndex, or similar.
- Cloud (AWS/GCP/Azure) and DevOps familiarity.
- Frontend experience (React, Vue) is a plus.
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