Job Description
Shape the Future of Work with Agentic AI
We are looking for a visionary Lead Agentic AI Architect to join Nexus Future Labs. As we prepare for the technological paradigm shift of 2026, we are building the next generation of autonomous AI agents capable of complex problem-solving and decision-making.
In this high-impact role, you will lead the architectural design of self-improving AI systems, integrating Large Language Models (LLMs) with autonomous workflows. You will work at the intersection of research and engineering, ensuring our solutions are scalable, secure, and revolutionary.
Why Join Us?
- Future-Forward Impact: Build the core infrastructure for the AI-native workforce of tomorrow.
- Top-Tier Compensation: Competitive salary plus equity package.
- Modern Tech Stack: Work with the latest in Python, Rust, and distributed systems.
If you are passionate about pushing the boundaries of AI autonomy and want to define the standards for 2026, we want to hear from you.
Responsibilities
- Design and implement advanced Agentic AI architectures capable of multi-step reasoning and autonomous tool usage.
- Lead the fine-tuning and optimization of Large Language Models (LLMs) for specific enterprise use cases.
- Collaborate with cross-functional teams to integrate AI agents into existing product ecosystems.
- Ensure the scalability, security, and ethical use of AI systems in production environments.
- Research emerging trends in Generative AI and Autonomous Systems to stay ahead of the 2026 roadmap.
- Mentor junior engineers and data scientists, fostering a culture of innovation and continuous learning.
Qualifications
- Experience: 7+ years of experience in software engineering, with at least 3 years focused on AI/ML or Machine Learning Engineering.
- Technical Expertise: Deep proficiency in Python and experience with frameworks like PyTorch or TensorFlow.
- AI Specialization: Proven track record working with LLMs (GPT-4, Claude, Llama) and frameworks such as LangChain, LlamaIndex, or AutoGen.
- System Design: Strong understanding of distributed systems, microservices, and cloud infrastructure (AWS/GCP).
- Problem Solving: Ability to architect complex, fault-tolerant systems that handle high concurrency.
- Education: Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, or a related field.