Job Description
Are you ready to define the technological landscape of 2026?
Nexus Future Systems is seeking a visionary Senior AI Architect to lead our core engineering team in designing the next generation of autonomous systems. If you are passionate about pushing the boundaries of Generative AI, Large Language Models (LLMs), and predictive analytics, we want to meet you.
As a key player in our Project 2026 initiative, you will not just write code; you will architect the future. You will be responsible for building scalable, fault-tolerant AI infrastructure that powers our global platforms. Join us in shaping the way the world interacts with intelligent machines.
Why Join Us?
- Work on cutting-edge technology that defines the future.
- Competitive compensation and equity package.
- Flexible remote-first work environment.
- Opportunity to mentor top-tier engineering talent.
Responsibilities
- Architect AI Infrastructure: Design and deploy scalable machine learning pipelines and AI architectures specifically tailored for the 2026 roadmap and beyond.
- Model Optimization: Fine-tune and optimize Large Language Models (LLMs) for high-performance inference and reduced latency in production environments.
- Strategic Planning: Collaborate with C-level executives to define the technical vision and implementation strategy for Project 2026.
- Code Review & Mentorship: Lead code reviews and mentor junior developers, fostering a culture of innovation and best practices.
- System Integration: Integrate AI solutions with existing cloud infrastructure (AWS/Azure) to ensure seamless data flow and operational efficiency.
- Ethical AI: Ensure all AI models adhere to ethical guidelines, bias mitigation standards, and data privacy regulations.
Qualifications
- Education: Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, or a related technical field. PhD preferred.
- Experience: 7+ years of experience in software engineering with a focus on AI/ML, including 3+ years in a senior architectural or lead role.
- Technical Skills: Proficiency in Python, TensorFlow, PyTorch, or similar deep learning frameworks. Strong experience with distributed systems and cloud computing.
- Generative AI: Deep understanding of Generative AI models, LLMs (e.g., GPT-4, Claude), and prompt engineering strategies.
- Problem Solving: Demonstrated ability to solve complex, ambiguous technical problems and make data-driven architectural decisions.
- Communication: Excellent verbal and written communication skills with the ability to translate technical concepts to non-technical stakeholders.