• Partner closely with Product Managers and users across commercial and corporate functions to transform pain points and proposed solutions into actionable, well-scoped technical requirements for the development team. • Focus on designing and architecting automation and Artificial Intelligence (AI) solutions that streamline workflows, enhance productivity, and deliver measurable business value. • Collaborate with cross-functional teams to ensure technical feasibility, alignment with business goals, and successful delivery of innovative solutions. • Scope and document solution requirements, ensuring alignment with organizational strategy and technical best practices. • Design end-to-end solutions leveraging automation and AI to optimize business processes and drive operational efficiency. • Facilitate technical discovery sessions and workshops with stakeholders to clarify requirements, constraints, and success criteria. • Develop architectural diagrams, technical blueprints, and integration plans to guide implementation. • Guide and support development teams throughout the solution lifecycle, ensuring quality, security, and scalability standards are met. • Validate delivered solutions against business requirements, coordinating with Product Managers and stakeholders for acceptance testing and feedback. • Maintain comprehensive documentation and contribute to a library of best practices for requirements scoping and solution delivery.

• Design, build, and deploy AI/ML solutions using GCP Vertex AI, BigQuery ML, and AI Platform for model training, deployment, and serving • Develop and maintain platform services for AI agent orchestration, RAG pipelines, and LLM integration using Python, FastAPI, and Flask • Collaborate with cross-functional teams to support CI/CD pipelines for ML models, GitLab workflows, and MLOps automation • Work with GCP services including Cloud Functions, Cloud Run, Dataflow, and Pub/Sub to build event-driven AI architectures • Build and optimize data pipelines using BigQuery, Dataflow, and Apache Airflow for AI model training and inference • Contribute to automation, observability, and reliability initiatives for AI systems using GCP Cloud Operations and New Relic • Lead and mentor team members in AI/ML engineering best practices, fostering a culture of learning and innovation • Explore and integrate cutting-edge AI capabilities (LLMs, vector databases, prompt engineering) into platform solutions • Develop customized AI solutions and integrations to meet development teams' requirements, leveraging GCP APIs, SDKs, and LangChain • Create technical documentation, tutorials, and training materials to support AI/ML adoption and facilitate knowledge transfer • Stay up to date on latest AI/ML technologies, GCP products, and industry trends, serving as a subject matter expert for the organization • Analyze existing AI workflows and processes to identify areas for optimization and efficiency gains • Implement scalable AI systems and tools to automate repetitive tasks, streamline ML operations, and enhance developer productivity

• Responsible for providing technical leadership for Coinstar’s enterprise applications with a focus on our ERP platform and core business systems • Identifying and resolving complex issues, strengthening and enhancing current solutions • Acting as a technical go-to for software engineers in developing solutions that support Coinstar’s corporate systems • Establishing standards and best practices for translating business requirement into full-stack development solutions across ERP and integrated applications • Collaborating in setting and implementing the overall organizational vision • Representing the Technology organization across the business to ensure functional alignment with strategic business goals • Participating in company long-range planning sessions • Managing vendors and enterprise Service Level Agreements (SLAs) • Maintaining all software development and operational documentation. • Providing technical direction to achieve Service-oriented Architecture (SOA) principles to build full-stack software solutions according to software engineering design best practices • Leading team attainment of velocity and productivity goals in project and time tracking tools

• Take ownership of daily cluster failures and issues, troubleshooting them promptly to maintain optimal cluster availability and performance. • Manage updates to the site controller management nodes. • Manage the rollout and rollback of cluster software and firmware updates, ensuring smooth transitions and minimal disruptions.