AI Software Engineer

KLA•Ann Arbor, MI

1d•$111,100 - $188,900•Onsite

About The Position

The AI Software Engineer will design and build AI-driven applications powered by large language models (LLMs), with a focus on integrating AI capabilities into user-facing products. This role emphasizes application development, orchestration, and user experience rather than model training. The engineer will develop scalable backend services, prototype intuitive user interfaces, and enable seamless interaction between users and LLM-based systems. This position requires a strong blend of software engineering, systems thinking, and practical AI implementation to deliver production-ready solutions that leverage LLM APIs and frameworks.

Requirements

Bachelor’s degree in Computer Science, Software Engineering, or related field
3+ years of professional software development experience
Strong programming skills in Python, JavaScript, or similar languages
Experience building and consuming RESTful APIs
Hands-on experience integrating LLM APIs or similar AI services into applications
Familiarity with prompt engineering and LLM interaction patterns
Experience developing web-based user interfaces (e.g., React, Angular, or similar frameworks)
Understanding of cloud platforms (e.g., Azure, Snowflake)
Knowledge of software design principles, version control, and CI/CD practices
Master’s Level Degree and related work experience of 6 years; OR Bachelor's Level Degree and related work experience of 8 years; OR equivalent work experience

Nice To Haves

Experience building AI products using LLM frameworks (e.g., LangChain, Semantic Kernel, LlamaIndex)
Knowledge of retrieval-augmented generation (RAG) and vector databases (e.g., Pinecone, FAISS, Azure Cognitive Search)
Vector database (Milvus) for semantic search, along with a knowledge graph (Neo4j)
Experience orchestrating multi-step AI workflows or agent-based systems
Familiarity with enterprise data platforms and integrations (e.g., Snowflake, SAP, APIs, knowledge graphs)
Experience designing conversational interfaces or chat-based applications
Understanding of evaluation techniques for LLM outputs (quality, grounding, hallucination mitigation)
Exposure to prompt optimization, fine-tuning concepts (not necessarily hands-on training)
Experience deploying scalable microservices architectures
Strong UI/UX sensibility for AI-driven applications
Experience working in cross-functional teams delivering production-grade AI solutions

Responsibilities

Design and develop end-to-end AI applications that leverage LLMs for business use cases
Build and maintain backend services that orchestrate LLM interactions, prompts, and workflows
Prototype and develop intuitive user interfaces that enable effective human-AI interaction
Integrate LLM APIs (e.g., OpenAI, Azure OpenAI, Anthropic) into scalable applications
Develop prompt engineering strategies and manage prompt lifecycle for performance and reliability
Implement retrieval-augmented generation (RAG) architectures using internal and external data sources
Design data pipelines and connectors to enterprise systems (e.g., databases, APIs, knowledge bases)
Monitor, evaluate, and improve AI application performance using metrics such as latency, cost, and response quality
Collaborate with product managers, data scientists, and business stakeholders to translate requirements into AI-enabled solutions
Ensure responsible AI practices, including privacy, security, and bias mitigation
Rapidly prototype AI tools and iterate based on user feedback