Job Description
We are building the infrastructure of tomorrow. Nexus Future Technologies is looking for a visionary Senior AI Architect to lead our groundbreaking research in Generative AI and Autonomous Systems. This is a unique opportunity to define the technical landscape for 2026 and beyond.
In this pivotal role, you will architect scalable, secure, and ethical AI systems that solve real-world problems. You will bridge the gap between cutting-edge theoretical research and production-grade engineering, ensuring our solutions are robust, efficient, and ready for global deployment.
What You Will Do:
- Lead the architectural design of Next-Gen Large Language Models (LLMs) and multimodal agents.
- Implement reinforcement learning from human feedback (RLHF) pipelines to enhance model alignment and safety.
- Optimize model inference latency and cost-efficiency using advanced edge computing techniques.
- Establish best practices for AI ethics, governance, and compliance.
- Collaborate with cross-functional teams to integrate AI capabilities into core product ecosystems.
- Conduct code reviews and mentor junior engineers in advanced AI engineering techniques.
Why Join Nexus Future Technologies?
- Work on projects that shape the future of the industry.
- Competitive compensation and equity packages.
- Flexible remote-first culture with premium office amenities in downtown SF.
Responsibilities
- Design and deploy advanced Generative AI architectures for complex enterprise solutions.
- Lead the research and implementation of Agent-based workflows and autonomous systems.
- Optimize model inference latency and cost-efficiency using edge computing techniques.
- Establish best practices for AI ethics, safety, and compliance in model training pipelines.
- Collaborate with cross-functional teams to integrate AI capabilities into core product ecosystems.
- Conduct code reviews and mentor junior engineers in advanced AI engineering techniques.
- Stay ahead of emerging trends in Large Language Models (LLMs) and multimodal AI.
Qualifications
- Master’s or PhD in Computer Science, Machine Learning, or a related technical field.
- Minimum of 7+ years of experience in software engineering, with at least 4 years specializing in AI/ML.
- Extensive experience with PyTorch, TensorFlow, or JAX.
- Strong proficiency in Python and cloud platforms (AWS, GCP, or Azure).
- Demonstrated success in deploying large-scale LLM applications in production environments.
- Deep understanding of distributed systems, microservices, and containerization (Docker/Kubernetes).
- Excellent communication skills and the ability to translate technical concepts for non-technical stakeholders.