Description

Key Responsibilities

• Design, build, and operate production AI applications using LLM APIs, RAG, tool/function calling, and deterministic business logic.
• Develop secure APIs, services, adapters, and event-driven integrations across digital channels and enterprise systems.
• Implement retrieval, ingestion, chunking, indexing, reranking, and citation workflows while preserving permissions and data boundaries.
• Create representative evaluation datasets, automated tests, and regression suites for groundedness, relevance, safety, and performance.
• Build and maintain CI/CD pipelines, structured logging, tracing, cost/health monitoring, and operational runbooks for AI services.
• Participate in production support, incident response, root-cause analysis, and continuous improvement with attention to security and responsible implementation.

Qualifications

• Typically 10+ years in professional software engineering or equivalent practical experience delivering AI, search, NLP, or data-intensive applications to production.
• Hands-on experience with LLM APIs, prompt/context design, embeddings, retrieval systems, structured outputs, and automated evaluation.
• Proficiency with SQL and document/search stores, containers, CI/CD, source control, cloud services, and observability practices.
• Strong software engineering habits: modular design, automated testing, secure coding, peer review, and performance troubleshooting.
• Ability to explain model limitations and engineering trade-offs to both technical and non-technical stakeholders.
• Bachelor's degree in computer science, engineering, data science, or equivalent practical experience preferred

Key Skills

Education

Bachelor's degree