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

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.