Job Description
Are you ready to shape the future of Artificial Intelligence?
Nexus Future Labs is seeking a visionary Senior AI Engineer to lead our Agentic AI division. As we move towards the 2026 era of autonomous systems, we are building intelligent agents capable of complex reasoning, self-correction, and autonomous decision-making. If you are passionate about the intersection of LLMs, multi-agent systems, and future-forward technology, this is your chance to build the foundation for the next generation of AI.
Why Join Us?
- Work on cutting-edge Agentic AI architectures.
- Shape the roadmap for autonomous systems in 2026.
- Competitive equity and salary package.
- Flexible remote-first culture.
Responsibilities
- Architect Agentic Systems: Design, implement, and deploy advanced multi-agent workflows that leverage Large Language Models (LLMs) for autonomous task execution.
- Model Optimization: Fine-tune and optimize foundation models for specific agentic behaviors, focusing on reasoning, memory, and tool use.
- System Integration: Integrate autonomous agents with external APIs, databases, and enterprise systems to create seamless intelligent workflows.
- Performance Engineering: Ensure high availability, low latency, and robust error handling for autonomous agent deployments in production environments.
- Research & Development: Stay ahead of the curve in AI research, specifically focusing on autonomous agent safety, alignment, and scalability.
- Collaboration: Partner with product managers and engineers to translate complex 2026 roadmap goals into technical specifications.
Qualifications
- Experience: 5+ years of experience in software engineering, with at least 3 years specializing in AI/ML or NLP.
- Technical Skills: Proficiency in Python, PyTorch, TensorFlow, or Hugging Face Transformers. Experience with LangChain or similar agent frameworks is required.
- AI Expertise: Deep understanding of LLMs, prompt engineering, and fine-tuning methodologies.
- System Design: Strong ability to design scalable distributed systems capable of handling complex logic.
- Problem Solving: Demonstrated ability to debug complex, multi-modal AI systems and resolve edge-case scenarios.
- Education: Bachelor’s degree in Computer Science, Engineering, or a related field (Master’s preferred).