Job Description
We are seeking a visionary Lead AI Architect to define the technological trajectory of our organization as we approach the 2026 landscape. In this pivotal role, you will be responsible for designing the core infrastructure that supports next-generation Generative AI and Autonomous Systems. You will bridge the gap between cutting-edge research and scalable production environments, ensuring our AI solutions are robust, secure, and future-ready.
Our ideal candidate is a thought leader who thrives in ambiguity and possesses a deep understanding of the rapidly evolving AI ecosystem. You will work closely with product managers, data scientists, and engineering teams to translate high-level business goals into technical roadmaps that define the next era of our products.
Responsibilities
- Design and implement scalable AI architectures specifically tailored for the 2026 market requirements and emerging technologies.
- Lead the strategic integration of Large Language Models (LLMs) and Agentic workflows into production environments.
- Oversee the entire machine learning lifecycle, from data ingestion and model training to deployment and monitoring.
- Mentor a team of talented engineers and data scientists, fostering a culture of innovation, code quality, and technical excellence.
- Conduct rigorous architectural assessments and code reviews to ensure system integrity, scalability, and performance.
- Stay ahead of emerging AI trends to advise executive leadership on long-term product roadmaps and investment opportunities.
- Collaborate with cross-functional teams to translate complex business needs into effective technical AI solutions.
Qualifications
- 10+ years of experience in software engineering and 5+ years in specialized AI/ML architecture.
- Deep expertise in Python, PyTorch, TensorFlow, or similar deep learning frameworks.
- Proven track record of deploying production-grade LLM applications, RAG systems, and Generative AI tools.
- Strong understanding of distributed systems, cloud architecture (AWS/Azure/GCP), and MLOps best practices.
- Excellent communication skills with the ability to explain complex technical concepts to non-technical stakeholders.
- Master’s degree in Computer Science, Machine Learning, or a related technical field is preferred.