Entry Level AI Software Engineer

About the Role

At IBM Software, you will help turn client challenges into solutions and build AI-powered, cloud-native products. The team values curiosity, collaboration and continuous learning, and offers room to advance your career while creating software that matters on a global scale.

At IBM Z, the technology supports the transactions and data behind banking, payments and global commerce. The team is bringing AI 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 your 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 take a feature from prototype through testing and refinement.

What You'll 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.

Required Skills

• Strong software engineering fundamentals, including data structures, algorithms, software design and testing.
• Proficiency in Python and experience building applications or services that integrate APIs.
• Hands-on experience building an application or working prototype with LLMs. You can explain what you built, how you integrated the model and how you tested its behavior. This experience may come from personal, academic, open-source or internship projects.
• A systematic debugging mindset, with the ability to investigate failures, test assumptions and reason about how application code, data, models and underlying systems interact.
• Ability to translate a problem into clear requirements, prompts and testable acceptance criteria, and to critically evaluate AI-generated code and responses.
• Familiarity with Git, clear technical communication, and the ability to learn quickly and collaborate on a team.

Preferred Skills

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 that show initiative and thoughtful engineering decisions.
• JavaScript/TypeScript or Go, and familiarity with distributed systems or microservices.
• Operating system concepts such as concurrency, multithreading and memory management, plus relational databases and SQL.
• Cloud and container technologies such as Docker, Kubernetes or OpenShift, and observability, search or real-time data processing tools such as OpenSearch or Kafka.
• AI evaluation, anomaly detection, or experience 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.