• Ship full-stack features that meet quality and UX standards; • Deliver well-crafted user experiences that solve user problems; • Lay solid technical foundations and contribute to architecture decisions; • Integrate Microsoft APIs reliably; • Build a quality culture by establishing testing practices; • Grow the team's collective level through code reviews and knowledge sharing; • Leverage AI coding tools to enhance development output.

• Leading the design and implementation of critical platform components for Akamai Inference Cloud, ensuring performance, scalability, and reliability • Driving technical decisions for your domain, selecting appropriate tools, frameworks, and approaches for AI inference workloads • Mentoring and guiding engineers on the team through code reviews, design discussions, and technical problem-solving • Implementing and optimizing containerized AI workloads with hardware-specific optimizations and integrating inference frameworks at scale • Collaborating across teams to define technical requirements, contribute to platform standards, and ensure operational excellence

• Analyze, design, and implement features. • Develop Microservice Oriented Architecture & build reusable components. • Write well-designed, efficient, and testable code, using AI coding tools to accelerate implementation while maintaining code quality standards and performing unit and integration tests. • Analyze performance and reliability to ensure that data is moving fast and accurately. • Perform identification of code metrics and necessary analysis (code, requirements, system risk, and software reliability). • Correct anomalies and problems as they arise. • Test the implemented features to make sure all acceptance criteria are met • Review code and provide guidance to other engineers to ensure that software is developed with maintainability, performance and security in mind. • Participate in projects from the initial idea to launch. • Advise the product owner on technological choices and decisions concerning developments. • Contribute to the continuous improvement of development velocity, including AI-assisted testing, automated deployment pipelines, and LLM-augmented code review practices. • Review the security/reliability implications of software design decisions. • Collaborate with the security team to integrate security best practices into software development processes. • Communicate risks associated to any activity, technology or processes as you identify them. • Participate in incident response activities and work with the infrastructure and security teams to investigate and remediate incidents.

• Define and lead the technical and architectural vision for our core platform. • Drive AI and machine learning initiatives that power automation, compliance, and data intelligence. • Embed DevSecOps and security-first principles throughout our software delivery lifecycle. • Design scalable, resilient, and cloud-native systems that support our global operations. • Mentor senior engineers, cooperate with Engineering managers, and guide teams toward engineering excellence. • Collaborate with Product, Data, and AI teams to deliver intelligent, secure, and high-performing solutions.