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Robert Half is hiring! We are looking for an Artificial Intelligence (AI) Engineer to create and deliver intelligent capabilities that strengthen a SaaS product within the finance consulting space. This position partners with product, data, and engineering teams to turn business needs into practical AI and machine learning solutions. The ideal candidate brings strong hands-on experience with production ML systems, a thoughtful approach to scalable architecture, and a focus on building features that improve user outcomes and operational efficiency. The best candidate for this role is someone that is still a hands on coder. We are looking for back end software engineers that also have skills and a passion for AI.
Job Responsibility:
Create and launch AI and machine learning solutions that support product functionality, workflow automation, and data-driven decision-making across the platform
Build end-to-end ML workflows that cover data preparation, feature development, model training, validation, deployment, and ongoing performance oversight
Collaborate with product managers, software engineers, and data professionals to identify high-impact use cases for intelligent automation and advanced analytics
Develop generative AI applications such as content summarization, recommendation engines, classification tools, and agent-based experiences while balancing response speed, quality, and operating cost
Connect trained models to cloud-based production environments through APIs, service-oriented components, and containerized deployment patterns
Assess external AI platforms, libraries, and vendor solutions to determine their value for product enhancement and engineering productivity
Apply responsible AI practices by supporting model stability, bias awareness, data privacy, and security expectations throughout the development lifecycle
Maintain clear technical documentation, structured experiment records, and repeatable development processes that support transparency and collaboration
Track emerging trends in machine learning, large language models, and SaaS engineering to recommend improvements to tools, architecture, and delivery methods
Requirements:
Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a closely related field, or equivalent practical experience
At least 3 years of experience designing, deploying, and supporting machine learning models in production environments
Strong Python development skills along with experience using machine learning frameworks such as PyTorch, TensorFlow, or scikit-learn
Background working with cloud platforms such as AWS, Google Cloud, or Azure, plus container technologies including Docker and Kubernetes
Familiarity with large language models, vector databases, and contemporary AI tooling used for applied machine learning solutions
Understanding of API development and service-based architecture within modern software applications
Solid foundation in software engineering principles, including algorithms, data structures, code quality, and maintainable system design
Experience with model experimentation, evaluation practices, and monitoring approaches for production AI systems