Job Description
We are seeking a visionary Senior AI Systems Architect to lead the technical roadmap for 2026. At Nexus Future Labs, we are building the foundational infrastructure for the next generation of autonomous agents and large-scale generative models. You will bridge the gap between theoretical AI research and production-grade engineering, ensuring our systems are ready for the enterprise demands of the future.
Key Objectives:
- Architect scalable, high-performance inference pipelines for Large Language Models (LLMs) designed for the 2026 market.
- Optimize model latency and throughput using custom kernels and hardware acceleration (GPU/FPGA).
- Lead the design of fault-tolerant distributed training clusters capable of processing petabytes of data.
- Define and enforce best practices for AI safety, ethics, and governance.
- Collaborate with product leaders to translate 2026 strategic goals into technical specifications.
- Conduct technical due diligence for AI acquisitions and strategic partnerships.
Qualifications:
- Master’s degree or PhD in Computer Science, AI, or a related technical field.
- 8+ years of experience in software engineering, with at least 4 years in AI/ML infrastructure.
- Deep expertise in Python, C++, and Rust.
- Experience deploying models at scale on cloud platforms (AWS, GCP, or Azure).
- Strong understanding of Transformer architectures and optimization techniques.
- Proven track record of leading engineering teams in a fast-paced, high-velocity environment.
Responsibilities
- Architect scalable, high-performance inference pipelines for Large Language Models (LLMs) designed for the 2026 market.
- Optimize model latency and throughput using custom kernels and hardware acceleration.
- Lead the design of fault-tolerant distributed training clusters.
- Define and enforce best practices for AI safety, ethics, and governance.
- Collaborate with product leaders to translate 2026 strategic goals into technical specifications.
- Conduct technical due diligence for AI acquisitions and partnerships.
Qualifications
- Master’s degree or PhD in Computer Science, AI, or a related technical field.
- 8+ years of experience in software engineering, with at least 4 years in AI/ML infrastructure.
- Deep expertise in Python, C++, and Rust.
- Experience deploying models at scale on cloud platforms (AWS, GCP, or Azure).
- Strong understanding of Transformer architectures and optimization techniques.
- Proven track record of leading engineering teams in a fast-paced, high-velocity environment.