Job Description
We are looking for a visionary AI Architect (2026 Roadmap) to lead our engineering efforts in shaping the future of intelligent systems. As we look toward the horizon of 2026, our goal is to pioneer breakthroughs in Generative AI, Autonomous Agents, and Cognitive Computing. You will be at the forefront of defining the technical strategy that drives our next generation of products, ensuring we remain ahead of the curve in an evolving technological landscape.
Why Join Us?
At Nexus Future Labs, we are not just building software; we are architecting the future. We offer a competitive salary, equity packages, and a remote-first culture that values autonomy and innovation. If you are passionate about pushing the boundaries of what is possible with AI, we want to hear from you.
Responsibilities
- Architect and implement scalable, high-performance AI systems designed for the 2026 landscape, focusing on robustness and scalability.
- Lead the research and development of Large Language Model (LLM) fine-tuning, prompt engineering, and deployment strategies.
- Define the long-term technical roadmap and ensure alignment with business objectives and market trends.
- Mentor senior engineers and foster a culture of innovation, technical excellence, and continuous learning.
- Collaborate closely with product management to translate complex AI capabilities into user-centric, high-impact solutions.
- Optimize model inference latency and cost-efficiency for edge deployment and cloud environments.
- Evaluate emerging technologies and frameworks to ensure our stack remains cutting-edge.
Qualifications
- Master’s degree or PhD in Computer Science, Mathematics, or a related field with a heavy focus on AI/ML.
- 5+ years of experience in designing, building, and deploying production-level machine learning systems.
- Deep proficiency in Python, TensorFlow, PyTorch, or JAX.
- Extensive experience with LLMs (e.g., GPT, Llama, Claude) and Retrieval-Augmented Generation (RAG) architectures.
- Strong understanding of distributed systems, cloud infrastructure (AWS/GCP), and MLOps pipelines.
- Exceptional problem-solving skills and the ability to thrive in a fast-paced, agile startup environment.
- Strong communication skills, with the ability to articulate complex technical concepts to non-technical stakeholders.