• Take a comprehensive view of the ASIC development lifecycle, identifying cross-stage bottlenecks and opportunities where automation and AI can improve predictability, convergence, and turnaround time. • Identify, curate, and leverage real-time data to enable effective AI models and analytics, working with infrastructure teams to ensure scalable and secure data pipelines. • Establish quantitative metrics to measure efficiency, quality, and cycle-time improvements; use data-driven insights to guide methodology decisions and prioritize investments. • Serve as a technical catalyst within both the team and the wider company by sharing best practices, publishing internal guidelines, and mentoring engineers on emerging AI-enabled development techniques. • Track advances in AI, EDA, and hardware design research, evaluating their applicability and guiding strategic bets that align with long-term product and technology roadmaps.

• Act as a senior technical escalation point during production incidents • Lead real-time incident triage, mitigation, and recovery efforts • Drive root cause analysis (RCA) with a focus on systemic, long-term fixes • Identify recurring failure patterns and push for architectural or operational improvements • Partner with Customer Success and Engineering to manage customer impact during incidents • Own post-launch reliability, stability, and operational quality of core systems • Investigate and resolve complex field issues and production defects • Ensure fixes developed during incidents or customer escalations are up streamed into the core product • Improve operational readiness of services through better runbooks, monitoring, and alerting • Reduce operational toil by converting repeated manual work into automation • Engage directly with strategic customers to solve real-world, production-grade technical challenges • Support complex deployments, integrations, and escalations in customer environments • Act as a trusted technical partner to customers during high-impact issues • Translate customer learnings into concrete product, platform, and operational improvements • Contribute to reusable tools, playbooks, and best practices that accelerate future deployments • Serve as a subject matter expert for AWS-hosted production systems • Troubleshoot and resolve issues across: • AWS compute, storage, networking, IAM, and security • Databricks jobs, clusters, and Spark-based data pipelines • Debug performance degradation, scalability issues, job failures, and data correctness problems • Partner with platform and data teams to harden systems for reliability, scale, and operability • Write production-quality code to: • Automate operational workflows • Improve reliability and observability • Eliminate manual intervention and reduce incident frequency • Contribute primarily in Python, with exposure to JVM-based systems as needed • Review code with a strong emphasis on operability, resiliency, and maintainability • Provide technical leadership without formal authority, influencing design and operational decisions • Mentor engineers through pairing, reviews, and incident leadership • Collaborate closely with Product, Engineering, Data, and Customer teams • Operate effectively in high-pressure, ambiguous environments, especially during customer-impacting incidents

• Data gathering, validation and analysis. • Assist with the creation of MOPs (Method of Procedures), SOPs (Standard Operating Procedures) and EOPs (Emergency Operating Procedures). • Replicate MOPs, SOPs, EOPs across the platform where similar equipment exists. • Work with existing Facility Engineers to update equipment records. • Collaborate with Compliance team members who will provide direction, feedback, and mentorship throughout the internship.

• Design, develop, and maintain scalable backend services using Node.js. • Build and manage microservices following clean architecture principles. • Implement event-driven and asynchronous processing solutions in AWS. • Define infrastructure as code using CloudFormation. • Ensure high-quality code through testing and best development practices. • Collaborate closely with cross-functional teams, contributing to product and business discussions.