Job Description
Shape the Future of Intelligence.
Are you ready to architect the next generation of artificial intelligence? FutureScale Technologies is seeking a visionary Senior AI Architect to lead our strategic 2026 roadmap. In this pivotal role, you will define the technical vision for our next-gen LLM platforms and generative AI solutions, bridging the gap between cutting-edge research and scalable production engineering.
We are looking for a thought leader who thrives in ambiguity and is obsessed with building robust, ethical, and high-performance systems. Join us in defining the standard for AI in 2026 and beyond.
Why Join Us?
- Impact: Directly influence the trajectory of AI technology used by millions.
- Innovation: Work with state-of-the-art models and distributed systems.
- Equity: Competitive equity package tied to company success.
Your Mission:
As the Senior AI Architect, you will own the technical strategy for our 2026 product suite, ensuring our infrastructure is ready for the next wave of AI advancements.
Responsibilities
- Define the 2026 Architecture: Design and oversee the implementation of scalable, fault-tolerant AI infrastructure that supports our long-term product vision.
- Model Optimization: Lead the strategy for optimizing large language models (LLMs) for specific enterprise use cases, focusing on latency and cost-efficiency.
- R&D Leadership: Evaluate emerging AI technologies and frameworks, making architectural decisions that keep us ahead of the curve.
- Cross-Functional Collaboration: Partner with product managers, data scientists, and engineering leads to translate business requirements into technical roadmaps.
- Security & Ethics: Implement robust guardrails and safety protocols to ensure responsible AI deployment.
- Team Mentorship: Mentor junior engineers and architects, fostering a culture of technical excellence and continuous learning.
Qualifications
- Experience: 8+ years of software engineering experience, with at least 5 years specifically in AI/ML architecture and large-scale system design.
- Technical Expertise: Deep understanding of Machine Learning principles, NLP, and Generative AI models (e.g., GPT, BERT, Llama).
- Programming: Proficiency in Python, C++, and experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX.
- Infrastructure: Strong experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
- Education: MS or PhD in Computer Science, Mathematics, or a related field is strongly preferred.
- Soft Skills: Exceptional communication skills with the ability to explain complex technical concepts to non-technical stakeholders.