Job Description
Are you ready to build the foundation for the next era of artificial intelligence? Synthetix Future Labs is seeking a visionary Senior AI Architect to define our roadmap through 2026 and beyond. In this pivotal role, you will lead the design of scalable, ethical, and high-performance AI systems that will redefine industry standards. We are not just looking for a coder; we are looking for a strategic partner who can navigate the complexities of Generative AI, Large Language Models (LLMs), and next-gen neural networks.
As we prepare for the transformative year of 2026, you will be at the forefront of innovation, ensuring our infrastructure is robust enough to handle the exponential growth of intelligent applications. If you thrive in a fast-paced, high-impact environment and want to leave a lasting legacy in the tech world, we want to hear from you.
Responsibilities
- Architectural Vision: Lead the design and implementation of core AI infrastructure, ensuring scalability and reliability for 2026 and future tech stacks.
- Model Optimization: Oversee the fine-tuning and deployment of Large Language Models (LLMs) and generative AI agents to maximize performance and reduce latency.
- Strategic Roadmap: Define the technical roadmap for AI adoption, identifying emerging technologies and integrating them into our product ecosystem.
- Cross-Functional Leadership: Collaborate with data scientists, product managers, and engineers to translate complex business requirements into technical solutions.
- Ethical AI Compliance: Establish and enforce frameworks for responsible AI, ensuring data privacy, bias mitigation, and ethical usage of intelligent systems.
- Talent Mentorship: Mentor junior engineers and architects, fostering a culture of continuous learning and technical excellence within the AI division.
Qualifications
- Experience: 8+ years of experience in software engineering, with at least 5 years specifically focused on AI/ML architecture and system design.
- Technical Stack: Proficiency in Python, PyTorch, TensorFlow, and modern deep learning frameworks. Strong understanding of distributed systems (Kubernetes, Docker).
- Cloud Expertise: Extensive experience designing scalable architectures on major cloud providers (AWS, Azure, or GCP).
- AI Specialization: Deep knowledge of Natural Language Processing (NLP), Computer Vision, or Reinforcement Learning.
- Problem Solving: Demonstrated ability to solve complex technical problems and make high-impact architectural decisions.
- Communication: Exceptional verbal and written communication skills, capable of bridging the gap between technical and non-technical stakeholders.