Job Description
We are building the foundation for the digital ecosystem of 2026. Apex Future Systems is seeking a visionary Senior Generative AI Architect to lead the next generation of adaptive intelligence solutions. You will define how machines understand, generate, and interact with human language in complex, real-world environments.
In this role, you will not just use existing models; you will architect the future of AI, ensuring scalability, safety, and ethical deployment at a massive scale.
Why join us?
- Impactful Work: Shape the trajectory of AI technology for the next decade.
- State-of-the-Art Tools: Access to top-tier GPUs and proprietary datasets.
- Remote-First Culture: Flexible work environment for global talent.
Responsibilities
- Architect LLM Pipelines: Design and implement scalable architecture for Large Language Models and multimodal systems.
- Model Optimization: Fine-tune and optimize models for latency, cost-efficiency, and accuracy in production environments.
- Prompt Engineering Strategy: Develop advanced prompting frameworks and retrieval-augmented generation (RAG) strategies to enhance model output quality.
- Ethical AI Governance: Implement guardrails and safety measures to ensure AI outputs are unbiased and compliant with emerging regulations.
- Team Leadership: Mentor junior engineers and data scientists, fostering a culture of innovation and continuous learning.
- Research & Development: Stay ahead of the curve on the latest breakthroughs in generative AI, including diffusion models and reinforcement learning from human feedback (RLHF).
Qualifications
- Education: Master’s degree or PhD in Computer Science, Machine Learning, or a related quantitative field.
- Experience: 5+ years of professional experience in software engineering or AI research.
- Technical Skills: Proficiency in Python, PyTorch, TensorFlow, and modern deep learning frameworks.
- Model Mastery: Deep understanding of Transformer architectures, BERT, GPT, and diffusion models.
- Problem Solving: Proven track record of solving complex optimization problems and improving model performance metrics.
- Communication: Excellent written and verbal communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.