Software Developer - Spring Co-Op 2027 - Cambridge

At IBM Software, we transform client challenges into solutions. Building the world’s leading AI-powered, cloud-native products that shape the future of business and society. Our legacy of innovation creates endless opportunities for IBMers to learn, grow, and make an impact on a global scale. Working in Software means joining a team fueled by curiosity and collaboration. You’ll work with diverse technologies, partners, and industries to design, develop, and deliver solutions that power digital transformation. With a culture that values innovation, growth, and continuous learning, IBM Software places you at the heart of IBM’s product and technology landscape. Here, you’ll have the tools and opportunities to advance your career while creating software that changes the world. This is a 16-week Co-op position designed for actively enrolled undergraduate students who are interested in gaining hands-on, practical experience while contributing to real IBM engineering projects. To be eligible, candidates must be currently enrolled at an accredited university and able to pause their coursework for the duration of the Co-op, as students may not be enrolled in classes while participating. This role requires full-time availability (40 hours per week) during the Spring 2027 semester between January 19 and May 7, 2027. Eligible candidates should also be available to join IBM in a full-time role between December 2027 and August 2028 upon successful completion of their degree. We are looking for Software Developer Co-op students to join an engineering team building technologies for AI agents, large language models, evaluation, observability, optimization, and cloud-native AI systems. As a Co-op student, you will work alongside experienced IBM engineers to design, build, test, and operate software used to understand and improve the behavior of AI applications. Depending on the project, you may contribute to SDKs, APIs, distributed backend services, developer tools, user interfaces, or infrastructure. This role is designed for students who are passionate about software engineering and interested in the rapidly evolving intersection of AI, cloud infrastructure, distributed systems, and developer platforms. Prior experience with AI agents is not required. We value strong software fundamentals, technical curiosity, and the ability to learn quickly. You will gain hands-on experience working on production systems, modern cloud-native technologies, and engineering challenges associated with deploying and improving AI applications at scale. What You’ll Do • Support the design, development, testing, and debugging of software across front-end, back-end, infrastructure, and full-stack environments. • Build capabilities that help developers evaluate, observe, debug, benchmark, and optimize AI agents and generative AI applications. • Work with large language models and AI agents to analyze behaviors such as tool usage, responses, execution traces, latency, quality, and cost. • Help develop automated evaluation and testing systems for AI applications, including test-case generation, behavioral metrics, benchmarking, and regression testing. • Build services and APIs that collect, process, and analyze telemetry and evaluation data from distributed AI applications. • Contribute to SDKs and integrations that connect with different AI models, agent runtimes, and development frameworks. • Explore techniques for improving the quality and efficiency of AI systems through prompt optimization, model selection, tool optimization, and automated experimentation. • Work with a variety of programming languages depending on the project, including Python, Java, JavaScript, TypeScript, C++, Go, Rust, Swift, Kotlin, or others. • Help build user interfaces using frameworks such as React, or contribute to backend services, APIs, and distributed systems. • Work with cloud and container technologies such as Docker, Kubernetes, REST APIs, and cloud-native services. • Use Git and other version-control, CI/CD, and collaboration tools. • Participate in code reviews, technical design discussions, Agile development, and collaboration with engineers, researchers, product managers, and designers. • Explore emerging technologies in agentic AI, LLM evaluation, observability, optimization, automation, and cloud-native development. Location Flexibility By applying to this requisition, you acknowledge and agree to be considered for any of the listed locations associated with this position and are willing to work at the location where you are ultimately assigned. • Must be actively enrolled in a Bachelor’s degree program at the time of application and returning to complete the degree after the Co-op. • Available to start full-time between December 2027 and August 2028. • Available to work full-time 40 hours per week at an IBM location for 16 weeks between January 19 and May 7, 2027. • The Co-op requires a full-time commitment; students should not be enrolled in concurrent coursework during the Co-op term. Transferable skills and experience from coursework, internships, research, personal projects, or open-source contributions are encouraged. • Coursework or project experience in software development using at least one programming language. • Familiarity with fundamental computer science concepts such as data structures, algorithms, debugging, APIs, and software design. • Exposure to front-end or back-end technologies such as React, Node.js, Python, Java, SQL, Go, or similar technologies. • Experience using Git or a similar version-control system. • Interest in AI systems, large language models, AI agents, cloud computing, containers, distributed systems, or developer tooling. • Strong analytical thinking, problem-solving, and communication skills. • Ability to collaborate effectively and learn new technologies quickly in a team environment • Experience experimenting with large language models, generative AI, or AI agents. • Familiarity with AI or agent development frameworks such as LangGraph, LangChain, LlamaIndex, or similar technologies. • Exposure to concepts such as LLM evaluation, tracing, observability, benchmarking, prompt engineering, or model optimization. • Experience with cloud services such as IBM Cloud, AWS, Azure, or GCP. • Familiarity with REST APIs and relational or NoSQL databases. • Experience with Docker, Kubernetes, or other container technologies. • Familiarity with observability technologies such as OpenTelemetry, distributed tracing, metrics, and logging. • Exposure to CI/CD pipelines, automation tools, or cloud-native deployment practices. • Personal, research, or open-source projects that demonstrate creativity, initiative, and technical curiosity. • Understanding of Agile software development methods.