About the Role
Northwestern Mutual is seeking a Software Engineer III to join a team focused on transforming our servicing applications through Agentic AI. In this role, you will design, build, deploy, and support full-stack AI-powered solutions that improve servicing experiences, operational efficiency, and business outcomes.
This position is ideal for a software engineer with hands-on production experience developing AI and Generative AI solutions who enjoys solving complex business problems through modern engineering practices. You will work across the full software development lifecycle, applying Agentic AI technologies, cloud-native architectures, and software engineering best practices to deliver scalable, secure, and reliable solutions.
You will collaborate closely with engineers, product teams, architects, and business stakeholders to take solutions from concept through production while helping the team evolve its AI development capabilities, technical standards, and engineering practices.
What You Will Do
- Design, build, test, deploy, and support Agentic AI and Generative AI solutions in production environments.
- Develop scalable APIs, microservices, and full-stack applications that integrate AI capabilities into business workflows.
- Partner with product, engineering, and business teams to identify opportunities where AI can drive business value.
- Leverage modern software engineering practices including test automation, code reviews, design patterns, and continuous integration.
- Develop and support cloud-native applications and services utilizing AWS technologies and modern architecture patterns.
- Contribute to DevOps practices including CI/CD pipelines, monitoring, observability, release management, and production support.
- Troubleshoot complex technical and production issues while identifying sustainable long-term solutions.
- Participate in architecture discussions and provide recommendations for scalable, secure, and maintainable solutions.
- Establish and share engineering best practices, standards, and AI development approaches across the team.
- Mentor engineers through technical guidance, collaboration, code reviews, and knowledge sharing.
What You Will Bring to the Role
- Bachelor's degree in Computer Science, Engineering, or equivalent experience.
- 5+ years of professional software engineering experience building enterprise applications.
- Demonstrated experience developing, deploying, and supporting AI and Generative AI solutions in production environments.
- Strong software engineering fundamentals including object-oriented design, APIs, microservices, design patterns, and testing strategies.
- Experience developing and supporting cloud-native applications utilizing AWS or similar cloud platforms.
- Experience implementing DevOps practices including CI/CD, automated testing, release management, and operational support.
- Strong architecture, debugging, troubleshooting, and technical problem-solving skills.
- Understanding of application security principles, authentication, authorization, and secure development practices.
- Ability to communicate technical concepts effectively with both technical and non-technical audiences.
- Demonstrated ability to lead technical initiatives, mentor team members, and influence engineering best practices.
- Experience working within Agile software development environments.
Nice to Have
- Experience with Agentic AI frameworks and orchestration platforms.
- Experience with Retrieval-Augmented Generation (RAG) architectures.
- Experience integrating Large Language Models (LLMs) into enterprise applications.
- Experience with prompt engineering, model evaluation, and responsible AI practices.
- Experience with containerization technologies such as Docker and Kubernetes.
- Experience with serverless architectures and event-driven systems.
- Experience building observability and monitoring solutions for AI-enabled applications.
- Exposure to AI-assisted software development tools and practices.
- Prior technical leadership or solution architecture experience.
Skills You Have
- AI & Generative AI Engineering: Designs, develops, deploys, and supports AI and Generative AI solutions in production environments. Applies knowledge of Agentic AI, LLMs, prompt engineering, model evaluation, retrieval-based solutions, and responsible AI practices to solve business problems and improve engineering outcomes.
- Software Engineering: Designs, develops, tests, maintains, and supports scalable software applications throughout the full software development lifecycle. Applies modern engineering practices including APIs, microservices, design patterns, automated testing, and code quality standards.
- Cloud-Native Engineering: Develops and supports cloud-native applications utilizing AWS and modern cloud platforms. Applies distributed systems, serverless computing, containerization, observability, and scalable architecture principles.
- DevOps & Production Support: Implements CI/CD pipelines, automated testing, deployment processes, monitoring, and operational support practices that improve delivery speed, reliability, and system performance.
- Architecture & Technical Problem Solving: Evaluates technical challenges, analyzes system dependencies, identifies root causes, and develops effective solutions that balance business needs, scalability, security, and maintainability.
- Application Security: Integrates security practices throughout the software development lifecycle, including authentication, authorization, secure coding, vulnerability management, and protection of sensitive customer and business data.
- Adaptive Communication: Communicates effectively with engineers, product teams, architects, leadership, and business stakeholders to drive alignment, influence decisions, and deliver successful business outcomes.
- Technical Leadership & Mentoring: Provides technical guidance, mentorship, code reviews, and knowledge sharing while promoting engineering excellence, collaboration, and continuous improvement across the team.
- Learning Agility & Innovation: Continuously evaluates emerging technologies, AI capabilities, and engineering practices while demonstrating curiosity, adaptability, ownership, and a commitment to ongoing learning and innovation.
Compensation Range:
Pay Range - Start:
$108,160.00
Pay Range - End:
$162,240.00
Geographic Specific Pay Structure:
Structure 110:
$118,960.00 USD - $178,440.00 USD
Structure 115:
$124,400.00 USD - $186,600.00 USD
We believe in fairness and transparency. It’s why we share the salary range for most of our roles. However, final salaries are based on a number of factors, including the skills and experience of the candidate; the current market; location of the candidate; and other factors uncovered in the hiring process. The standard pay structure is listed but if you’re living in California, New York City or other eligible location, geographic specific pay structures, compensation and benefits could be applicable, click here to learn more.
Grow your career with a best-in-class company that puts our clients' interests at the center of all we do. Get started now!
Northwestern Mutual is an equal opportunity employer that welcomes talented individuals of all backgrounds. We are committed to creating and maintaining an environment in which each employee can contribute creative ideas, seek challenges, assume leadership and continue to focus on meeting and exceeding business and personal objectives.