Jobs › Northwestern Mutual

Software Engineer III

Northwestern Mutual · Franklin, WI · Full time

Posted Sep 29, 2026 · We last checked this listing on Oct 6, 2026

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Likely interview questions for this role

Written from this job description, not a generic list. Each one notes what the interviewer is really checking.

About your past

Tell me about an agentic AI or generative AI solution you put into production. What went wrong after launch?

What they are checking: Whether they have real production experience with AI, which the posting requires.

Tell me about a time you helped your team adopt a new technical practice.

What they are checking: Whether they can help evolve engineering standards and AI capabilities on the team.

Describe a time you took a feature from concept all the way to production.

What they are checking: Whether they own the full lifecycle and work well with product and business partners.

What would you do

A business partner wants AI for a problem that a simple rule would solve. What do you do?

What they are checking: Whether they choose the right tool and give honest advice about where AI adds value.

About the work

How would you design an AI agent that helps a servicing rep complete a policy change?

What they are checking: Whether they can design tools, guardrails and human review into an agent workflow.

How do you evaluate whether an LLM-based feature is accurate enough to ship?

What they are checking: Whether they build evaluation sets and testing instead of judging by a few demos.

What are the main risks of using generative AI in a regulated financial company, and how do you reduce them?

What they are checking: Whether they think about privacy, hallucination and auditability in a regulated setting.

Walk me through how you would build an API that integrates an AI capability into an existing business workflow.

What they are checking: Whether they can connect AI to real systems with sound microservice design.

How do you monitor an AI feature in production for cost, latency and quality?

What they are checking: Whether they know how to support AI systems after deployment, not just build them.

How do you handle prompt or model changes so they do not break things already working?

What they are checking: Whether they apply version control and regression testing to AI components.

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The full job description

As published by Northwestern Mutual.

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.

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