SAPSenior Backend Developer for Cloud FinOps (Typescript/NodeJS Focus)

• Learn to review and break down work items into tasks with stakeholder collaboration, provide estimations, and escalate delays, while also supporting feature deployments to customers, considering user and service impacts, and adhering to best deployment practices for safety.  • Collaborate with key stakeholders to define feature requirements, integrate feedback to enhance design, and establish feedback loops for continuous improvement based on customer metrics.  • Learn and apply coding standards and best practices through code reviews, developing maintainable and extensible code with guidance. Utilize debugging tools to proactively and reactively address issues in product features, ensuring code quality and reliability.  • Support the identification of dependencies and design documentation for product features, learn about system interactions and back-end dependencies, and contribute to architectural processes under guidance. Produce code to test hypotheses for technical solutions and assist with technical validation efforts. Collaborate on quality assurance plans, augment test cases, and integrate automation into testing, while understanding the implications of security and compliance in system architecture.  • Contribute to data analysis and feedback integration for product engineering decisions, acting as a Designated Responsible Individual (DRI) for monitoring and restoring system functionality within Service Level Agreement (SLA) timeframe. Participate in live service operations, and support telemetry data integration for system behavior insights, with a focus on performance, reliability, and safety.  • Develop and apply best practices for reliable code building, understand global and local regulations, customer scaling requirements, and support communication with key partners across Microsoft for user experience enhancement and partner needs.  • Ensure compliance with security, privacy, safety, and accessibility standards, leverage developer tools for code creation and debugging, contribute to automation in production and deployment, and proactively seek knowledge to improve product availability, reliability, efficiency, and performance at scale. 

• Design, build, and harden containers for NIM runtimes, inference backends; enable reproducible, multi-arch, CUDA-optimized builds. • Develop Python tooling and services for build orchestration, CI/CD integrations, Helm/Operator automation, and test harnesses; enforce quality with typing, linting, and unit/integration tests. • Help design and evolve Kubernetes deployment patterns for NIMs, including GPU scheduling, autoscaling, and multi-cluster rollouts. • Optimize container performance: layer layout, startup time, build caching, runtime memory/IO, network, and GPU utilization; instrument with metrics and tracing. • Evolve the base image strategy, dependency management, and artifact/registry topology. • Collaborate across research, backend, SRE, and product teams to ensure day-0 availability of new models. • Mentor teammates; set high engineering standards for container quality, security, and operability.

Design and develop AI-driven applications, delivering scalable, user-focused solutions across web and mobile platforms.Build and maintain robust, cloud-based architectures, ensuring seamless integration of front-end and back-end systems with AI models.Prototype and implement new features, leveraging analytics, user insights, and market trends to improve product quality and user experience.Collaborate with product managers, designers, and data scientists to align technical solutions with product strategies and business goals.Drive technical innovation by exploring new technologies and frameworks, ensuring system performance, maintainability, and scalability.Mentor and support junior engineers, fostering a culture of collaboration, learning, and continuous improvement.

About TI As a global semiconductor company, we design, manufacture, test and sell analog and embedded processing chips to nearly 100,000 customers. Our products enable electronics everywhere and in things you experience every day - from health care, smart homes and connected cars to drones, smart phones and more. Our passion to create a better and more sustainable world by making electronics more affordable through semiconductors drives us to make our technology smaller, more efficient, more reliable and more affordable. About the Job The AI Engineer will drive implementation of artificial intelligence and machine learning solutions to enhance semiconductor back-end manufacturing operations. The role will involve close collaboration with manufacturing teams, data scientists, product and process engineers to identify opportunities and implement AI-driven solutions that improve operational efficiency, quality, and yield. This position requires a strong understanding of AI/ML technologies, experience with semiconductor manufacturing, and a passion for applying data-driven techniques to solve complex industrial problems. Responsibilities include: • Collaborate with cross-functional teams and domain experts to identify opportunities for AI integration in workflows. • Analyze and preprocess large datasets from manufacturing equipment, sensors, and logs to enable effective machine learning applications. • Lead proof-of-concept projects and pilot programs to demonstrate the value of AI applications in manufacturing settings. • Develop and deploy AI/ML models for defect detection, yield improvement, process optimization, and predictive maintenance in semiconductor back-end manufacturing processes. • Provide technical documentation, training, and support to ensure seamless adoption of AI solutions by production teams. • Monitor AI systems performance and implement enhancement. Stay updated with the latest advancements in AI/ML and propose innovative solutions applicable to semiconductor manufacturing.