Entry Level AI Software Engineer

About the Role

At IBM Software, client challenges become working solutions. The team builds AI-powered, cloud-native products that shape how business and society operate. IBMers have room to learn, grow, and make an impact on a global scale. Working in Software means joining a team driven by curiosity and collaboration, with diverse technologies, partners, and industries.

At IBM Z, the technology supports the transactions and data behind banking, payments, and global commerce. AI is being brought into that foundation to help developers build faster, simplify complex operations, and solve problems where reliability, security, and performance matter.

As an Entry Level AI Software Engineer, you will work alongside experienced engineers to turn advances in large language models into useful software. Depending on the team, you could build an agent that helps diagnose system issues, connect AI to enterprise data and tools, or create a simpler way for developers to work with complex systems. You will help take a feature from prototype through testing and refinement.

What You Will Do

• Design, build, and test AI-powered features that address real developer and client needs, with guidance from experienced engineers.
• Integrate LLMs, APIs, and enterprise data into applications, exploring agent workflows, tool calling, and retrieval where they fit the problem.
• Write clear specifications and effective prompts, use AI development tools thoughtfully, and review and test the code they produce.
• Evaluate AI behavior with realistic test cases, measure quality and performance, and improve how applications handle incorrect outputs and failures.
• Debug across model interactions, application code, APIs, and underlying systems to find root causes and build reliable solutions.
• Collaborate through Git, code reviews, and technical discussions, document your work, and iterate on feedback.

Location Flexibility

By applying to this requisition, you 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.

Nice to Have

Experience in one or more of the following areas is a plus. You do not need experience with every technology listed.

• AI agents, tool or function calling, retrieval-augmented generation (RAG), embeddings, vector databases, or Model Context Protocol (MCP).
• Independent AI projects, open-source contributions, or experiments beyond assigned coursework.
• JavaScript/TypeScript or Go, and familiarity with distributed systems or microservices.
• Operating system concepts such as concurrency, multithreading, and memory management; relational databases and SQL.
• Cloud and container technologies such as Docker, Kubernetes, or OpenShift; observability, search, or real-time data processing tools such as OpenSearch or Kafka.
• AI evaluation, anomaly detection, or measuring and improving model accuracy, latency, and reliability.

Where available, include a project link, repository, demo, or a brief description of your contribution and the technical challenges you worked through.