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Mutual of Omaha · 4 hours ago

Senior AI Developer

Full-time

Hybrid

Senior Level, Lead/Staff

$130K/yr - $180K/yr

8+ years exp

Mutual of Omaha is seeking a Senior AI Developer to transform their enterprise through the design, development, and deployment of AI and genAI applications. This role involves leading AI/ML projects, collaborating across systems, and ensuring the integration of technical solutions with operational needs.

Auto InsuranceCommercial InsuranceFinancial ServicesHealth InsuranceInsuranceLife InsuranceProperty Insurance

No H1B

Responsibilities

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

Qualification

AI DevelopmentMLOpsAWS InfrastructureFull-Stack DevelopmentPythonCI/CD PipelinesData ScienceMachine LearningAgile MethodologiesCollaborationProblem SolvingCommunication

Required

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

Proven in-depth AI knowledge

Experienced in AWS services, particularly Bedrock, SageMaker, S3, and Lambda

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