Job Description
Are you ready to architect the digital future of 2026?
Apex Future Systems is pioneering the next generation of intelligent solutions. We are seeking a visionary Senior Generative AI Engineer to lead the development of cutting-edge Large Language Model (LLM) applications. If you thrive in a fast-paced, high-impact environment and want to define the standard for AI in the coming years, this is your opportunity.
Join us in Austin to build scalable, secure, and ethical AI systems that will redefine industry standards.
Responsibilities
- Architect & Develop: Design and implement robust, scalable generative AI pipelines using state-of-the-art frameworks (PyTorch, TensorFlow, Hugging Face).
- Model Optimization: Fine-tune and optimize large language models for specific enterprise use cases, focusing on latency, throughput, and cost-efficiency.
- RAG Implementation: Spearhead the development of Retrieval-Augmented Generation (RAG) architectures to enhance knowledge accuracy and reduce hallucinations.
- System Integration: Integrate AI models into existing microservices and cloud infrastructure (AWS/Azure/GCP) ensuring seamless data flow and API reliability.
- Mentorship: Lead a team of data scientists and engineers, conducting code reviews and fostering a culture of innovation and technical excellence.
- Ethical AI: Ensure all AI solutions adhere to strict ethical guidelines, data privacy regulations, and bias mitigation strategies.
Qualifications
- Education: Master’s or PhD in Computer Science, Artificial Intelligence, or a related quantitative field.
- Experience: 5+ years of professional software engineering experience, with at least 2+ years specifically in AI/ML model development and deployment.
- Technical Skills: Deep expertise in Python, experience with deep learning libraries (PyTorch, TensorFlow), and familiarity with vector databases (Pinecone, Milvus).
- Frameworks: Proven experience implementing and fine-tuning LLMs (GPT-4, Llama, Claude, Mistral).
- Cloud Native: Strong understanding of containerization (Docker, Kubernetes) and cloud-native development patterns.
- Problem Solving: Exceptional ability to troubleshoot complex system issues and optimize performance under load.