Senior AI Developer - Remote

The Senior AI Developer will lead the design, development, and deployment of AI and Generative AI applications, bridging technical solutions with business needs. This role requires deep expertise in AI, MLOps, DevOps, full-stack development, and AWS infrastructure. The developer will drive end-to-end AI/ML projects, mentor peers, and ensure secure, scalable, and reliable applications using CI/CD best practices. A strong collaborator and problem solver, this professional thrives in dynamic environments and plays a key role in delivering impactful, enterprise-wide innovation.WHAT YOU'LL DO:● Lead the design, development, and deployment of Generative AI and LLM applications by immersing yourself in the needs of operational areas to build empathy for business challenges and applying engineering best practices to build innovative, robust and reliable solutions that meet their needs.● Develop and maintain AWS infrastructure, with a focus on cloud resource management, security, and cost optimization. Prioritize security and fairness throughout the development and deployment process to protect our customers.● Collaborate on systems design and integration with both front-end and back-end (including legacy) systems, ensuring smooth operation and scalability. Maintain production reliability, CI/CD pipelines, and automated testing to support continuous delivery.Lead the end-to-end lifecycle of AI/ML projects. Improve accuracy by employing systematic experimentation, prompt engineering, data and training versioning, and A/B testing to empirically optimize model performance. Implement MLOps best practices to streamline the lifecycle of AI models.● Lead iterative delivery using agile methodologies, incorporating feedback and fostering a culture of continuous improvement to rapidly develop, test, and refine solutions. Own solutions from end-to-end through prototyping to production. Stay updated on advancements in genAI, cloud technologies, and ethical considerations in AI.WHAT YOU’LL BRING:● Bachelor’s degree in Computer Science, Engineering, or analytical fields (Mathematics, Data Science, etc.), or equivalent experience, with at least 8 years deploying and supporting full-stack applications in enterprise environments, and several years of experience integrating AI, MLOps into full-stack applications.● Experienced in full-stack development (backend, frontend, and database technologies) with expertise in frameworks like React or Flask, and strong skills in Python, TypeScript, git, SQL, CI/CD pipelines, automated testing, and DevOps best practices.● Experienced in AWS services, particularly Bedrock, SageMaker, S3, Lambda, and infrastructure as code (CDK). Extensive experience applying software engineering design patterns and enterprise application architecture principles to build secure, scalable, maintainable, and cost-optimized cloud-native applications.● Experienced in data science, machine learning techniques, and data engineering. Skilled at addressing fairness in AI development and applying experimentation and A/B testing methodologies to empirically evaluate and improve model performance.● Strong communicator and collaborator, experienced at building partnerships in remote and ever-changing environments. Resilient and resourceful problem solver, proactive at overcoming obstacles to achieve goals. Comfortable with ambiguity and change, demonstrating high learning agility, adapting quickly to shifting priorities, and bringing clarity to undefined problems.● You promote a culture of diversity and inclusion, value different ideas and opinions, and listen courageously, remaining curious in all that you do.● Able to work remotely with access to a high-speed internet connection and located in the United States or Puerto Rico.PREFERRED:● Advanced degree in an analytical field.● Familiarity with single or multi-cloud agentic architecture for building LLM-based applications.● Proven experience with MLOps and implementing automated pipelines for model and algorithm training, monitoring, versioning, deployment, and scaling in production environments.