• Prepare client recommendations, proposals, and quotes; develop solution sets. • Develop, document, and communicate recommended plans for Azure/AWS cloud data platform/infrastructure, including analysis of cost reduction opportunities. • Conduct research on emerging technologies in support of infrastructure development efforts, and recommend technologies that will increase cost effectiveness and infrastructure flexibility. • Develop objectives and strategies, and ensure all documentation is properly maintained and updated in a timely manner. • Responsible for planning activities that define the information needs of the enterprise and designing the master data blueprints to meet those needs within the context of all enterprise data architecture and the connections with information systems, information technologies, and solutions.

• Design, develop, and maintain high-performance, modular, and scalable Java applications using Spring Boot 3.4.x. • Architect and implement cloud-native solutions, ensuring best practices for distributed systems, reliability, maintainability, and observability. • Integrate observability into applications, including metrics collection, distributed tracing, structured logging, and proactive monitoring. • Collaborate with cross-functional teams to deliver robust RESTful APIs and microservices. • Optimize application performance, memory usage, and reliability. • Lead and mentor junior engineers, performing code reviews and setting engineering best practices. • Integrate and utilize AI coding assistants (such as GitHub Copilot or similar tools) to accelerate development and improve code quality. • Contribute to the evolution of our architecture and technology stack with a focus on modern Java, modularization, cloud technologies, and observability. • Ensure security, compliance, and observability of all deployed services. • Participate in Agile development processes, including planning, estimation, and retrospectives.

• Lead technical workshops to identify, refine, and prioritize high-impact AI and GenAI use cases aligned with business objectives. • Translate business problems into system design requirements and AI workflows. • Assess existing data platforms, pipelines, governance, and accessibility for AI workloads. • Evaluate data quality, lineage, security, and suitability for training, RAG, and inference patterns. • Design AI architectures that comply with enterprise security, privacy, and regulatory constraints (PII, PHI, internal policies). • Evaluate and design integrations across APIs, event streams, and existing systems. • Evaluate and recommend foundation models and AI services, including Amazon Bedrock, Amazon Nova, and open-source models. • Analyze tradeoffs across cost, latency, accuracy, and scalability. • Design GenAI patterns such as RAG, agent workflows, and inference pipelines. • Produce high-level and detailed AWS reference architectures for prioritized AI use cases. • Define phased implementation roadmaps that balance speed, risk, and long-term maintainability. • Identify PoC scope that can be executed within a short engagement. • Partner with stakeholders to develop ROI and TCO models for AI initiatives. • Provide cost modeling for model usage, data pipelines, infrastructure, and operations. • Deliver AI assessment findings and recommendations. • Create target-state AI platform architecture diagrams. • Summarize data readiness and compliance assessments. • Provide model evaluation and selection rationale. • Define phased implementation roadmap. • Design and validate PoC. • Prepare executive-ready presentations and documentation.

• Design and improve backend services that support complex business workflows. • Build and evolve distributed systems using modern cloud-native patterns. • Architect and implement event-driven and asynchronous workflows. • Collaborate closely with Salesforce, data, and product teams to ensure system reliability and scalability. • Improve performance, observability, and fault tolerance of existing systems. • Contribute to architectural decisions and long-term technical strategy. • Remain hands-on in coding while participating in design discussions.