Job Description
We are seeking a visionary Senior AI Architect to lead the technological roadmap for our 2026 initiatives. As we prepare to redefine the future of enterprise intelligence, you will be at the forefront of integrating Generative AI, Large Language Models (LLMs), and autonomous agents into scalable infrastructure. This is not just a coding role; it is a strategic leadership position where your architectural decisions will shape the company's trajectory for the next decade.
Why Join Us?
- Work on cutting-edge AI systems designed for the 2026 era.
- Competitive compensation and equity packages.
- Flexible, remote-first culture with a focus on innovation.
The Role
You will be responsible for designing, building, and maintaining the core AI infrastructure that drives our products. You will bridge the gap between theoretical AI research and practical, production-grade applications, ensuring our systems are robust, secure, and future-proof.
Responsibilities
- Architect LLM Infrastructure: Design and implement scalable systems for training and deploying Large Language Models, optimizing for the high-throughput demands of 2026.
- Autonomous Agent Development: Lead the engineering of AI agents capable of complex decision-making and multi-step reasoning in dynamic environments.
- Model Optimization: Apply advanced quantization and pruning techniques to reduce latency and improve inference speed on edge devices.
- AI Governance: Establish frameworks for ethical AI usage, ensuring fairness, transparency, and safety in all automated systems.
- Cross-Functional Leadership: Collaborate with product managers and data scientists to translate business goals into technical AI roadmaps.
- R&D Integration: Stay ahead of the curve by integrating emerging 2026-era technologies such as Multimodal AI and Neural Symbolic Computing.
Qualifications
- Education: Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related field.
- Experience: 7+ years of experience in software engineering, with at least 3 years specializing in AI/ML architecture.
- Technical Stack: Proficiency in Python, PyTorch, TensorFlow, and distributed computing frameworks (Kubernetes, Docker).
- AI Expertise: Deep understanding of NLP, transformers, and reinforcement learning. Experience with fine-tuning models (e.g., GPT, LLaMA) is required.
- System Design: Proven track record of designing high-availability, low-latency systems handling petabyte-scale data.
- Communication: Excellent verbal and written skills with the ability to explain complex AI concepts to non-technical stakeholders.