Job Description
Shape the Future of Intelligence with OmniTech Dynamics
We are on the cutting edge of technological evolution, and we need a visionary Lead AI Architect (2026 Visionary) to guide our engineering team. As we prepare for the next generation of Generative AI and Autonomous Systems, we are looking for a technical leader who can bridge the gap between complex research and scalable production solutions. If you thrive in a fast-paced environment and want to define the roadmap for AI capabilities in 2026, we want to hear from you.
Why Join Us?
- Work on groundbreaking projects that will define the AI landscape of tomorrow.
- Competitive salary and equity package in the heart of the tech hub.
- Access to state-of-the-art hardware and cloud infrastructure.
Role Overview
The Lead AI Architect will be responsible for the high-level design of our AI systems, ensuring they are robust, scalable, and ready for the demands of 2026. You will lead a team of talented data scientists and engineers, driving innovation in Large Language Models (LLMs), Vector Databases, and Agentic workflows.
Responsibilities
- Architectural Leadership: Design and oversee the implementation of scalable AI infrastructures, focusing on LLM orchestration and Retrieval-Augmented Generation (RAG) pipelines.
- Technical Roadmap: Define the strategic technical roadmap for AI capabilities, anticipating trends and preparing the stack for future advancements.
- Model Optimization: Drive initiatives to optimize model performance, reduce latency, and maximize throughput for real-time applications.
- Collaboration: Partner with Product Managers and Engineering teams to integrate advanced AI models into core product ecosystems seamlessly.
- Best Practices: Establish and enforce industry-standard best practices for data privacy, ethical AI, and responsible model deployment.
Qualifications
- Experience: 8+ years in software engineering, with at least 5 years specifically focused on Machine Learning and AI research/production.
- Languages: Proficiency in Python, with deep experience using PyTorch, TensorFlow, or JAX.
- LLM Expertise: Proven track record of deploying and fine-tuning Large Language Models (LLMs) in production environments.
- Vector DBs: Strong understanding of Vector Databases (e.g., Pinecone, Milvus, Weaviate) and Embedding strategies.
- Cloud & MLOps: Experience with MLOps tools (Docker, Kubernetes, MLflow) and major cloud platforms (AWS, GCP, or Azure).