Architect and evolve agentic in-app experiences that enable users to interrogate, explore, and act on data classification insights.
Develop scalable data classification pipelines that process documents, metadata, and records across systems using LLMs, embeddings, retrieval-augmented generation, and deterministic heuristics to accurately classify data and flag risks.
Implement observability and feedback loops that monitor model performance, enable human-in-the-loop validation, and continuously improve accuracy over time.
Develop APIs, services, and systems that extend and enhance our data privacy and permissioning platform.
Collaborate with product management and customers to understand customer challenges and translate them into technical solutions.
Ensure high code quality and maintain best practices in CI/CD, testing, and deployment pipelines.
Requirements
Proven experience designing and scaling backend systems in Python or Go, building APIs and data pipelines with a strong foundation in system design, testing, CI/CD, and cloud deployment.
Experience developing AI systems leveraging large language models, agentic frameworks (e.g., LangChain, PydanticAI), and RAG pipelines for context-grounded reasoning over enterprise data.
Familiarity with prompt engineering, fine-tuning, and evaluation methods for improving real-world model performance.
Experience instrumenting observability, tracking model metrics, and designing feedback loops for human-in-the-loop validation.
Ability to collaborate with product, design, and frontend teams to translate AI capabilities into intuitive user experiences.
Demonstrated ability to learn new technologies and apply them in practical contexts.
A degree in Computer Science or a related field, or equivalent work experience.
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
PythonGoAPIsdata pipelinessystem designCI/CDcloud deploymentlarge language modelsprompt engineeringfeedback loops