• Architect and develop full-stack applications that align with EDC’s AI & Digital Transformation strategy and drive high-priority business outcomes • Implement modular “Lego-block” architectures that are reusable and interoperable across business development, programmatic, and core business systems through API-first, cloud-native solutions • Integrate responsible AI by leveraging AWS Bedrock, CrewAI, and other AI services to design and deploy agentic AI teams and intelligent solutions • Streamline enterprise workflows by replacing manual processes with reliable, scalable, and automated digital systems • Collaborate cross-functionally with business development, program, and operations teams to translate business needs into scalable technical products • Ensure security, privacy, and accessibility by upholding EDC’s data governance and compliance standards across all solutions • Contribute to the Reference Architecture for Agentic AI which will serve as the blueprint for deploying and governing AI agents safely, efficiently, and at scale • Mentor and share knowledge across engineering and AI/Data communities to promote best practices in cloud-native, AI-enabled design • Continuously improve development processes through automation, observability, and agile, iterative delivery that reflects EDC’s learning culture

• Lead the Architecture and Development of full-stack applications that align with EDC’s AI & Digital Transformation strategy and drive high-priority business outcomes. • Establish and steward engineering standards for cloud-native, API-First, and AI-enabled development, including CI/CD practices, testing patterns, observability, and security. • Define and implement modular “Lego-block” architectures that are reusable and interoperable across business development, programmatic, and core business systems through API-first, cloud-native solutions. • Integrate responsible AI by leveraging AWS Bedrock, CrewAI, and other AI services to design and deploy agentic AI teams and intelligent solutions. • Streamline enterprise workflows by replacing manual processes with reliable, scalable, and automated digital systems. • Evaluate technical tradeoffs and provide clear recommendations on build vs. buy, short-term vs. long-term solutions, and architectural risk. • Collaborate cross-functionally with business development, program, and operations teams to translate business needs into scalable technical products. • Ensure security, privacy, and accessibility by upholding EDC’s data governance and compliance standards across all solutions. • Contribute to the Reference Architecture for Agentic AI which will serve as the blueprint for deploying and governing AI agents safely, efficiently, and at scale. • Mentor and share knowledge across engineering and AI/Data communities to promote best practices in cloud-native, AI-enabled design. • Continuously improve development processes through automation, observability, and agile, iterative delivery that reflects EDC’s learning culture.

• Participate in development of end-to-end AI/ML projects—from research and design to deployment and ongoing maintenance—ensuring scalable, production-ready systems • Help implement robust ML pipelines and production-grade infrastructure to support high-volume workloads • Partner with cross-functional teams to integrate AI capabilities aligned with business goals and customer needs • Research and prototype novel AI/ML algorithms and techniques to drive innovation • Help establish best practices for AI/ML development, deployment, monitoring, and governance • Monitor model performance, scalability, and cost in production, and drive continuous optimization • Advocate for responsible AI—focusing on fairness, transparency, and data privacy

• Design, develop, and deliver full-stack features across Ruby and JavaScript applications • Own technical direction by evaluating trade-offs and recommending solutions • Collaborate cross-functionally with product managers, business analysts, QA, and engineering partners • Practice and promote Agile development methodologies • Participate in software releases, partner with QA on test plans • Troubleshoot and resolve production issues, perform root cause analysis • Provide level 3 production support for enterprise applications after release • Mentor and elevate other engineers through code reviews • Participate in the continuous evolution of engineering standards and workflows • Explore and apply AI capabilities into the platform