Job Description
Are you ready to architect the digital landscape of 2026?
Horizon 2026 Solutions is at the forefront of the AI revolution, pioneering next-generation autonomous systems and generative intelligence models. We are seeking a visionary Senior AI Engineer to lead our engineering division and define the technical roadmap for our upcoming product suite.
In this role, you will not just use existing tools; you will shape the future of how machines learn, reason, and interact with the world. Join us in building the infrastructure that powers the year 2026 and beyond.
Why join Horizon 2026?
- Impactful Work: Directly influence the trajectory of AI development in the enterprise sector.
- Future-Proof: Work on cutting-edge technologies including Agentic AI and Neural Symbolic Computing.
- Competitive Compensation: Top-tier salary and equity packages for industry leaders.
Apply today to become a key architect of the future.
Responsibilities
- Lead the design and implementation of scalable AI architectures, focusing on Agentic workflows and Large Language Models (LLMs).
- Optimize deep learning models for performance, latency, and throughput in high-traffic production environments.
- Collaborate with cross-functional teams of data scientists, product managers, and engineers to translate business requirements into technical solutions.
- Establish and enforce best practices for MLOps, including model versioning, CI/CD pipelines, and automated retraining.
- Mentor junior engineers and contribute to the technical roadmap for the 2026 product suite.
- Ensure ethical AI deployment by auditing models for bias and ensuring compliance with emerging regulations.
Qualifications
- PhD or Master’s degree in Computer Science, Mathematics, or a related technical field.
- 5+ years of professional experience in AI/ML engineering, with at least 2 years in a senior leadership or architect role.
- Deep expertise in Python, PyTorch, TensorFlow, or JAX.
- Proven track record of deploying large-scale machine learning models to production (AWS, GCP, or Azure).
- Strong understanding of distributed systems, cloud infrastructure, and containerization (Docker, Kubernetes).
- Experience with Vector Databases and RAG (Retrieval-Augmented Generation) architectures.