Senior Solutions Architect - Emerging Technologies (AI, GenAI, ML)

Our vision for the future is based on the idea that transforming financial lives starts by giving our people the freedom to transform their own. We have a flexible work environment and fluid career paths. We not only encourage but celebrate internal mobility. We also recognize the importance of purpose, well-being, and work-life balance. Within Empower and our communities, we work hard to create a welcoming and inclusive environment, and our associates dedicate thousands of hours to volunteering for causes that matter most to them. Chart your own path and grow your career while helping more customers achieve financial freedom.

Applicants must be authorized to work for any employer in the U.S. We are unable to sponsor or take over sponsorship of an employment visa at this time, including CPT/OPT.

Responsibilities

• Lead discovery with business and technology partners to understand objectives, constraints, current-state systems, and integration points.
• Document current-state architecture and define target-state designs including system context diagrams, component designs, integration patterns, and data flows.
• Design and modernize applications into cloud-compatible or cloud-native architectures using microservices, serverless, and event-driven patterns where appropriate.
• Create strategies, roadmaps, and migration designs for transitioning applications and data workloads to cloud platforms.
• Design AI and ML-enabled solutions, including model integration into products and business processes, and patterns for scalable inference and low-latency serving where needed.
• Design Generative AI solution patterns, such as retrieval-augmented generation, tool and API integration, prompt and context management, and evaluation approaches.
• Define reference architectures for AI platforms and enabling capabilities, such as data pipelines, feature and embedding generation, vector storage, model endpoints, and integration with enterprise APIs.
• Establish best practices for MLOps and AI operations, including model versioning, deployment, monitoring, drift detection, incident response, and cost management.
• Incorporate security-by-design practices into architectures, including identity and access controls, encryption, secrets management, secure networking, and audit logging.
• Partner with governance and risk stakeholders to ensure responsible AI considerations are incorporated, including privacy, explainability, safety, compliance, and model risk controls as applicable.
• Drive alignment and adoption of proposed solutions by clearly communicating tradeoffs, risks, and value and obtaining stakeholder alignment and governance approvals.
• Support teams responsible for testing and validation and help triage and resolve design-related issues found during development, UAT, or production.
• Perform other duties as assigned.

Requirements

• Bachelor’s degree in Computer Science, Information Systems, Engineering, Mathematics, Business, or equivalent practical experience.
• 5+ years of experience in agile software delivery environments with increasing architecture and design responsibility.
• Demonstrated experience designing distributed systems using microservices and/or serverless patterns.
• Experience designing and integrating AI and ML capabilities into applications, including model serving considerations and data dependencies.
• Experience with one or more languages such as Java, Python, Node.js, or Scala.
• Experience with data persistence technologies across SQL and NoSQL.
• Experience with at least one major cloud provider, AWS, Azure, or Google Cloud, and core cloud design patterns.
• Working knowledge of CI/CD pipelines and DevOps practices, including automated testing and deployment automation.
• Strong communication skills and ability to translate business needs into clear technical direction.

Skills

• Hands-on experience with GenAI and LLM solutions, including retrieval-augmented generation, embeddings, evaluation, and production monitoring.
• Experience with AI and ML platforms or services, such as AWS SageMaker, Amazon Bedrock, Azure AI, Azure OpenAI, or Google Vertex AI.
• Infrastructure-as-Code experience, such as Terraform or CloudFormation.
• Container and orchestration experience, such as Docker and Kubernetes, and cloud container platforms like ECS or EKS.
• Experience with vector databases and search technologies and associated indexing and retrieval patterns.
• Experience with enterprise observability, including centralized logging, tracing, metrics, alerting, and operational readiness.
• Database and procedural development experience, including PL/SQL, and strong data modeling concepts.
• Familiarity with responsible AI practices, governance controls, and security considerations specific to AI systems.

Benefits

• Medical, dental, vision and life insurance
• Retirement savings – 401(k) plan with generous company matching contributions (up to 6%), financial advisory services, potential company discretionary contribution, and a broad investment lineup
• Tuition reimbursement up to $5,250/year
• Business-casual environment that includes the option to wear jeans
• Generous paid time off upon hire – including a paid time off program plus ten paid company holidays and three floating holidays each calendar year
• Paid volunteer time — 16 hours per calendar year
• Leave of absence programs – including paid parental leave, paid short- and long-term disability, and Family and Medical Leave (FMLA)
• Business Resource Groups (BRGs) – BRGs facilitate inclusion and collaboration across our business internally and throughout the communities where we live, work and play. BRGs are open to all.

Pay

Base Salary Range $125,400.00 - $181,875.00

The salary range above shows the typical minimum to maximum base salary range for this position in the location listed. Non-sales positions have the opportunity to participate in a bonus program. Sales positions are eligible for sales incentives, and in some instances a bonus plan, whereby total compensation may far exceed base salary depending on individual performance. Actual compensation offered may vary from posted hiring range based upon geographic location, work experience, education, licensure requirements and/or skill level and will be finalized at the time of offer.