Job Description
Are you ready to architect the intelligence of tomorrow?
At Apex Future Systems, we are defining the roadmap for the next generation of artificial intelligence. We are seeking a visionary 2026 AI & Agentic Systems Engineer to lead the development of autonomous agents that redefine human-machine collaboration.
In this role, you won't just write code; you will engineer the fabric of the future. You will be at the forefront of the Agentic AI revolution, building systems that plan, execute, and learn with unprecedented autonomy.
Why Join Us?
• Shape the future of AI technology.
• Work with top-tier talent in a cutting-edge environment.
• Competitive compensation and equity packages.
If you are passionate about the intersection of advanced machine learning and scalable systems engineering, we want to hear from you.
At Apex Future Systems, we are defining the roadmap for the next generation of artificial intelligence. We are seeking a visionary 2026 AI & Agentic Systems Engineer to lead the development of autonomous agents that redefine human-machine collaboration.
In this role, you won't just write code; you will engineer the fabric of the future. You will be at the forefront of the Agentic AI revolution, building systems that plan, execute, and learn with unprecedented autonomy.
Why Join Us?
• Shape the future of AI technology.
• Work with top-tier talent in a cutting-edge environment.
• Competitive compensation and equity packages.
If you are passionate about the intersection of advanced machine learning and scalable systems engineering, we want to hear from you.
Responsibilities
- Architect and deploy scalable Agentic AI systems capable of autonomous decision-making.
- Optimize Large Language Model (LLM) inference pipelines for real-time performance.
- Integrate multimodal data streams (text, vision, audio) into unified agent workflows.
- Design robust fault-tolerance and safety mechanisms for autonomous agents.
- Collaborate with product teams to translate '2026' visions into technical roadmaps.
- Implement MLOps best practices to ensure continuous model improvement and deployment.
Qualifications
- PhD or Master’s degree in Computer Science, AI, or a related technical field.
- 5+ years of experience in Machine Learning Engineering or AI Architecture.
- Deep expertise in Python, PyTorch, or TensorFlow.
- Proven track record of designing distributed systems using Kubernetes or cloud-native architectures.
- Experience with prompt engineering and fine-tuning Large Language Models.
- Strong understanding of reinforcement learning and agent-based simulation.