Senior Software Engineer

This position will be based at our New York Campus and require a hybrid work environment: 2 days weekly onsite and 3 days weekly remote. Who we are Variable is the applied innovation team within Northwestern Mutual. Our mission is to experiment with emerging technologies and technical strategies to meaningfully influence our organization’s technology roadmaps and investments. We partner with teams from across the entire organization to bring emerging technology to forefront. We are committed to fostering a diverse, equitable, and inclusive environment that nurtures innovation. Our team provides a stable yet dynamic platform for personal and professional growth, allowing individuals to drive meaningful change throughout our organization. About the Role We are hiring a senior engineer to lead technical strategy work and to build the proofs of concept that give that strategy its evidence. The role sits between engineering, architecture, and the business. In a typical quarter you will shape the architecture for a new class of system, get architects, risk partners, and product owners aligned on a path none of them owns alone, write the recommendation that goes to senior leadership, and build enough of the system to show that the recommendation holds. The work today centers on AI systems in regulated environments: agentic workflows and automations; the API, authorization, and fraud controls that make them safe; evaluation of systems whose outputs are non-deterministic; and the governance that lets them run in production. You will work with vendor platforms as often as with code we write ourselves, and much of the job is discovering what enterprise systems can actually do and what it would take to change them. You have led, or owned a major workstream in, technical transformation programs inside a large, regulated organization. You know how enterprise systems, controls, and decision rights work, and you can still open an editor and have something working in days. You write clearly and persuasively, because most of your work will lean on influence and will travel as documents. What You'll Do Develop technical strategy for the enterprise's highest-uncertainty technology questions: what to build, what to buy, what to wait on, and what has to be true for each path to work. Design reference architectures for new classes of systems, with particular attention to authorization, data access, audibility, and failure modes in a regulated environment. Demonstrate business value, feasibility, and scale in every recommendation, and say plainly when an idea should stop. Build coalitions across enterprise architecture, risk, fraud, information security, legal, product, and operations. Write the decision documents that let those groups agree, run the working sessions, and carry disagreement without stalling the work. Scope proofs of concept as hypotheses with a success measure and a stopping rule, then build them: working software against real enterprise systems and vendor platforms, built to answer a specific question and then handed off or retired. Lead the enterprise's approach to evaluating and enabling non-deterministic systems: test sets, assertion-based scoring, model-graded evaluation calibrated against human judgment, and the monitoring that follows a system into production. Evaluate vendor platforms and make build, buy, or partner recommendations backed by evidence and fitted to the enterprise's constraints. Maintain gap registers and readiness assessments that tell leadership what stands between a proof of concept and production, with a short-term and a long-term option for each gap. Present findings and recommendations to senior leadership in writing and in short sessions, and hand completed work to the teams that will own it. Work daily with AI coding agents. Set up the repositories, tests, and harnesses that let them produce reliable work, and review what they produce critically. What You'll Bring to the Role 7+ years in software engineering, including inside a large, regulated organization. Systems and integration architecture as your core expertise: APIs, identity and authorization, systems of record, integration patterns, and the vendor platforms that sit between them. Shipped applications on large language model APIs, including tool use, structured outputs, retrieval, and multi-step agents, with working knowledge of how these systems fail (hallucination, prompt injection, tool misuse, drift) and how to measure them. Experience designing evaluation for AI systems, and enough statistics to read the results honestly. Production experience in Python and TypeScript, with the range to build a service, an integration, and a usable interface without waiting on anyone. Cloud infrastructure inside enterprise guardrails: identity, secrets, network constraints, infrastructure as code, and model access through managed services such as AWS Bedrock or Azure OpenAI. Integration of third-party platforms and SDKs, including exposing enterprise capabilities to agents through tool interfaces (MCP servers or equivalent) with least privilege. Security and privacy judgment for AI in financial services: handling of client data, least privilege for autonomous systems, auditability, and model risk. Fluency with AI coding tools as a daily working method, and the judgment to know when their output is wrong. Clear writing. You can turn a complicated technical situation into a two-page recommendation a senior leader can decide on. A record of aligning stakeholders who do not report to you, in an organization where no single person owns the decision. We work with: Python, TypeScript, AWS, Terraform, and frontier model APIs accessed through enterprise-managed services. We also dive deep into third-party platforms. We test, learn, share, and repeat. Preferred Qualifications Experience playing key roles in problem definition, architecture, creating organizational alignment, and delivering a working result. A record of finding an opportunity no one assigned you, making the business case, and delivering it. Experience carrying a proof of concept into a production pilot owned by another team, on custom-built and vendor platforms alike, including the readiness, control, and handoff work it required. Insurance, wealth management, or financial planning domain knowledge, including advisor-facing tools. AI governance and model risk management: continuous monitoring, drift detection, authorization models for autonomous systems, and the documentation auditors and regulators expect. Time in an architecture, strategy, or platform function at a large company, where your output was a implementable strategy. Experience codifying business processes or institutional knowledge for automation. A short account of an endeavor that failed and your assessment as to why and what you learned. Skills You'll Have Cross-Functional Collaboration: Partnering with product, business, architecture, infrastructure, security, and quality teams. Technical Leadership: Guiding technical decisions, mentoring engineers, and improving engineering practices. Software Architecture: Contributing to the high-level structure, design patterns, integrations, and technical standards of a software system. Software Engineering: Applying engineering principles and development practices to design, build, test, deploy, and maintain reliable software. Programming Language Expertise: Hands-on proficiency in the languages required by the team, such as Java, C#, Python, JavaScript, TypeScript, C++, or Go. Application Development: Designing, developing, testing, and maintaining applications that meet business and user needs. Systems Integration: Connecting internal or third-party applications, services, APIs, databases, and platforms. #LI-Hybrid Compensation Range: Pay Range - Start: $136,800.00 Pay Range - End: $205,200.00 Geographic Specific Pay Structure: Structure 110: $130,880.00 USD - $196,320.00 USD Structure 115: $136,800.00