Software Engineer
Software Engineer Backend (Java, Python \& Generative AI) Location: Austin, TX Job Summary STAFFXPERT LLC is seeking a Software Engineer Backend (Java, Python \& Generative AI) on behalf of our client in Austin, TX. This role is ideal for a highly skilled backend engineer with experience building scalable applications, developing AI/ML-powered solutions, and working within modern cloud environments. The ideal candidate will have strong expertise in Java and Python, along with hands-on experience in machine learning frameworks and backend system design. Key Responsibilities Design, develop, and maintain scalable backend systems and APIs using Java and Python. Build and integrate machine learning and AI-driven features into production applications. Develop and optimize ML pipelines, model training workflows, and deployment processes. Collaborate with cross-functional teams including engineering, product, and data teams to deliver high-quality solutions. Ensure backend services are reliable, secure, and scalable within cloud-based environments. Participate in architecture discussions, code reviews, testing, and system optimization initiatives. Troubleshoot and resolve performance, scalability, and reliability issues across applications and services. Required Qualifications Strong backend engineering experience with Java and Python. Experience developing RESTful APIs, microservices, and distributed systems. Hands-on experience with machine learning, including model development and training pipelines. Familiarity with modern ML frameworks such as PyTorch, TensorFlow, and scikit-learn. Experience working with cloud infrastructure and data processing tools. Ability to work independently while effectively collaborating with existing engineering teams. Strong verbal and written communication skills. Preferred Qualifications Experience with Generative AI, Large Language Models (LLMs), or AI-powered application development. Familiarity with Docker, Kubernetes, and CI/CD pipelines. Knowledge of vector databases, RAG architectures, or model deployment frameworks is a plus. Prior experience in high-growth or fast-paced engineering environments preferred.