Job Description
Are you ready to architect the technological landscape of tomorrow? OmniFuture Systems is seeking a visionary Future-Ready AI Architect to lead the design and implementation of scalable, cutting-edge artificial intelligence systems designed for the 2026 era and beyond.
In this pivotal role, you won't just maintain existing infrastructure; you will build the foundation for the next decade of innovation. We are looking for a thought leader who understands the trajectory of Generative AI, Agentic workflows, and Ethical Machine Learning to drive our strategic roadmap.
Why Join Us?
- Work with a forward-thinking team focused on long-term technological impact.
- Competitive compensation package including equity and performance bonuses.
- Flexible remote-first culture with state-of-the-art equipment.
- Opportunity to define the standards for AI safety and scalability.
Responsibilities
- Strategic Roadmapping: Define and execute the technical vision for AI infrastructure, anticipating trends for the 2026 landscape including multimodal models and autonomous agents.
- System Architecture: Design robust, fault-tolerant distributed systems capable of handling high-throughput inference and training workloads.
- Model Deployment: Oversee the deployment, fine-tuning, and optimization of Large Language Models (LLMs) and proprietary AI models on cloud infrastructure.
- RAG & Pipeline Design: Lead the implementation of Retrieval-Augmented Generation (RAG) pipelines to enhance model accuracy and data privacy.
- Cross-Functional Collaboration: Partner with product managers, data scientists, and engineering teams to translate business requirements into technical architecture.
- Ethical AI Governance: Establish guidelines and frameworks to ensure AI outputs are fair, unbiased, and compliant with evolving regulations.
Qualifications
- Education: Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, or a related technical field.
- Experience: 7+ years of experience in software engineering, with at least 3 years in Machine Learning Architecture or AI Engineering.
- Technical Proficiency: Deep expertise in Python, PyTorch, TensorFlow, or similar frameworks.
- Cloud Mastery: Proven experience designing systems on AWS, Azure, or GCP.
- AI Knowledge: Hands-on experience with LLMs (GPT-4, LLaMA, Claude), vector databases (Pinecone, Milvus), and MLOps tools.
- Problem Solving: Strong analytical skills with a focus on scalability, latency optimization, and cost efficiency.
- Soft Skills: Excellent communication skills with the ability to explain complex technical concepts to non-technical stakeholders.