About The Position

The Senior Solutions Architect provides technical leadership and designs complex solution architectures that support business strategy and streamline technology-enabled workflows. This role partners closely with business owners, product, data, and engineering teams to document current-state systems and design scalable, resilient, and secure cloud-based solutions. This position focuses on emerging technologies, including AI, Generative AI, and machine learning, and guides solutions from research and analysis through architecture, delivery support, and operational readiness.

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.

Nice To Haves

  • 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.

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

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.
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