Senior Manager, Site Reliability Engineer - Remote

We are seeking a highly experienced Senior Software Engineering Manager to lead the strategy, architecture, development, and delivery of next-generation AI-powered digital platforms, enterprise applications, and data products. This leader will be responsible for building and scaling high-performing engineering teams that deliver modern cloud-native applications, AI/ML solutions, intelligent automation, and enterprise data platforms.

The ideal candidate combines deep technical expertise with solid people leadership, driving engineering excellence, innovation, modernization, and AI adoption across the organization while aligning technology investments with business outcomes.

You'll enjoy the flexibility to work remotely * from anywhere within the U.S. as you take on some tough challenges. For all hires in the Minneapolis or Washington, D.C. area, you will be required to work in the office a minimum of four days per week.

- Lead and develop multidisciplinary engineering teams across software development, digital engineering, data engineering, AI/ML engineering, and platform engineering - Establish technical vision, engineering standards, architecture governance, and execution strategies for enterprise-scale applications and AI-enabled platforms - Drive engineering excellence through best practices in software development, DevOps, testing automation, observability, reliability, and operational readiness - Partner with executive leadership to define technology roadmaps, investment priorities, and long-term modernization strategies - Build and mentor high-performing engineering organizations, fostering innovation, accountability, and continuous learning - Manage engineering capacity planning, talent development, performance management, and organizational growth

- Lead modernization of legacy platforms into cloud-native, API-first, event-driven, and AI-enabled architectures - Define technology standards and reference architectures for enterprise application development - Oversee development and deployment of scalable web, mobile, digital, and backend platforms supporting business growth - Partner with architecture, infrastructure, security, and operations teams to ensure scalable, resilient, and cost-effective solutions - Drive adoption of microservices, containerization, cloud services, and modern software engineering practices - Lead the teams focusing on leveraging enterprise AI and data transformation initiatives that improve customer experience, operational efficiency, and business decision-making - Oversee the design and implementation of scalable digital, data platforms

- Guide the design of enterprise data lakehouse and distributed computing architectures - Oversee development and deployment of AI/ML solutions including:

- Fraud Detection & Prevention - Lending Underwriting & Risk Scoring - Customer Personalization & Recommendations - Predictive Analytics & Forecasting - Natural Language Processing (NLP) - Intelligent Process Automation

- AI Agents and Autonomous Workflows - Retrieval-Augmented Generation (RAG) - Vector Databases - Enterprise Knowledge Management - Intelligent Document Processing - Conversational AI Platforms

- Drive adoption of AI-assisted software engineering tools including GitHub Copilot, Claude Code, and similar developer productivity platforms - Establish engineering practices leveraging AI to improve: - Developer productivity - Code quality - Test automation - Documentation generation - Code reviews - Delivery velocity - Develop organizational standards, training programs, and governance frameworks for responsible use of AI development tools

- Collaborate with Product Management, Business Leaders, Enterprise Architecture, Security, and Operations teams to define strategic priorities and execute transformation initiatives - Serve as a trusted advisor to senior executives on AI, data, and digital transformation opportunities - Drive alignment across engineering teams and business stakeholders to ensure successful delivery of critical initiatives - Influence enterprise architecture decisions and technology investment strategies

- 12+ years of progressive experience in software engineering, application development, data engineering, or AI/ML solution delivery - 5+ years leading software engineering teams and enterprise-scale technology programs - Proven experience delivering large-scale digital transformation, cloud modernization, and AI/ML initiatives - Proven solid technical background in:

- Java, .NET, Python, SQL - SQL Server, Oracle - Databricks, Power BI - Distributed data processing platforms - Cloud-native application architectures

- Azure, AWS, or Google Cloud Platform - Data Lakehouse architectures - Spark, Kafka, Flink - REST APIs, Microservices, Event-Driven Architectures - CI/CD, DevOps, MLOps

- Experience building and scaling enterprise AI platforms and MLOps ecosystems. - Hands-on understanding of:

- PyTorch - TensorFlow - Scikit-Learn - Large Language Models (LLMs) - Small Language Models (SLMs) - AI Agents - RAG Frameworks - Vector Databases (FAISS, Pinecone, Chroma)

- Experience in financial services, fraud detection, risk management, underwriting, or regulated industries - Experience leading enterprise adoption of AI-powered software engineering tools and practices

*All employees working remotely will be required to adhere to UnitedHealth Group's Telecommuter Policy.

Pay is based on several factors including but not limited to local labor markets, education, work experience, certifications, etc. In addition to your salary, we offer benefits such as, a comprehensive benefits package, incentive and recognition programs, equity stock purchase and 401k contribution (all benefits are subject to eligibility requirements).

No matter where or when you begin a career with us, you'll find a far-reaching choice of benefits and incentives. The salary for this role will range from $112,700 to $193,200 annually based on full-time employment. We comply with all minimum wage laws as applicable.

Application Deadline: This will be posted for a minimum of 2 business days or until a sufficient candidate pool has been collected. Job posting may come down early due to volume of applicants.