Senior AI Developer - Omaha, NE

Mutual of Omaha

3d•$130,000 - $180,000•Remote

About The Position

As a Senior AI Developer, you will be at the forefront of transforming our enterprise through the design, development, and deployment of AI and genAI applications. This role calls for a multifaceted expert with a deep understanding of AI, MLOps, DevOps, and full-stack development who can seamlessly integrate technical solutions with operational needs. You will immerse yourself in the challenges faced by our operational areas, fostering strong collaborations to create innovative and reliable solutions. Your expertise in AWS infrastructure, security best practices, and CI/CD pipelines will be critical in building and maintaining our applications. You will lead AI/ML projects through their entire lifecycle, mentoring fellow data scientists and developers while promoting engineering excellence. This position demands a proactive problem solver who thrives in ambiguity and can adapt swiftly to changing priorities, making a significant impact in a dynamic environment. WHAT WE CAN OFFER YOU: Estimated Salary: Minimum: $130,000 - 180,000 plus annual bonus opportunity. 401(k) plan with a 2% company contribution and 6% company match. Work-life balance with vacation, personal time and paid holidays. See our benefits and perks page for details. Applicants for this position must not now, nor at any point in the future, require sponsorship for employment.

Requirements

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.

Nice To Haves

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.

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.