Generative AI Engineer

Job Title: Gen AI Engineer Location: Hybrid- Austin, TX - 78751 Job Type: Long-term Contract Job Description We are seeking an Application Engineer with Generative AI expertise to design and guide the implementation of advanced AI-driven applications and platforms. This role bridges enterprise architecture, software engineering, and AI innovation—ensuring our solutions are scalable, secure, and player- or employee-focused. As an Application engineer, you will work closely with product, engineering, data science, and infrastructure teams to design application architectures that integrate LLMs, RAG pipelines, and other GenAI technologies into the ecosystem. You’ll ensure solutions align with the global technology strategy while enabling experimentation and rapid innovation. Responsibilities • Develop scalable, secure, and high-performing applications that incorporate Generative AI technologies. • Partner with engineering, data, and product teams to translate business and creative needs into technical architectures. • Define standards, patterns, and reference architectures for AI-enabled applications. • Guide application modernisation initiatives, integrating cloud-native and AI-native approaches. • Ensure solutions comply with enterprise security, data privacy, and responsible AI principles. • Collaborate with enterprise architects to align AI-driven applications with broader technology strategy. • Provide thought leadership and mentorship in GenAI adoption, best practices, and emerging tools. • Evaluate new AI/ML technologies, frameworks, and vendors, advising on build vs. buy decisions. Qualifications • 8+ years of experience in application/software engineering, with a strong record of designing enterprise-scale solutions. • Well-versed with Generative AI technologies (e.g., LLMs, RAG, vector databases, prompt engineering). • Strong background in cloud platforms (AWS, Azure, or GCP) and microservices architecture. • Proficiency in modern programming languages (Python, Node.js, Java, or similar). • Familiarity with MLOps and AI integration patterns (model deployment, inference optimization, monitoring). • Strong understanding of enterprise security, compliance, and governance requirements. • Excellent communication skills, able to influence technical and business stakeholders alike.