Senior AI Engineer
cornerstone
Job Description
AI-Native Product Development
- Design and implement AI-first architectures, where machine learning and generative AI are foundational system components.
- Build and productionize ML and Generative AI workflows, including prompt engineering, retrieval-augmented generation (RAG), evaluation, and iteration.
- Develop end-to-end AI features, from data ingestion and feature engineering to inference and feedback loops.
- Partner with Product and UX teams to shape AI-driven user experiences, ensuring usability, explainability, and trust.
Prompt Engineering & Optimization
- Design, develop, and optimize prompt strategies for large language models to ensure accuracy, consistency, and relevance in production use cases.
- Implement prompt versioning, experimentation, and A/B testing to support rapid iteration and data-driven improvements.
- Continuously evaluate and refine prompts using offline evaluation, automated testing, and live telemetry to reduce hallucinations and improve output quality.
- Optimize prompt and model usage to balance response quality, latency, and cost efficiency at scale.
- Collaborate with UX and Product to align prompt behavior with user intent, tone, and experience expectations.
Engineering & Platform Excellence
- Develop scalable backend services using Java and/or Python, deployed in AWS cloud environments.
- Design and optimize API-driven architectures that integrate AI services securely and reliably across the platform.
- Work with SQL and NoSQL databases to support transactional and analytical workloads.
- Apply strong engineering fundamentals around performance, reliability, observability, and security.
- Contribute to architectural decisions that ensure long-term scalability and maintainability.
Leadership & Collaboration
- Provide technical leadership in AI and system design discussions.
- Mentor engineers and help raise the overall AI and engineering maturity of the team.
- Collaborate cross-functionally with Data Science, Platform, UX, DevOps, and Security teams.
- Influence technical roadmaps and align AI capabilities with Workforce AI product goals.