Senior AI Engineer
About The Position
Cornerstone OnDemand is seeking a Senior AI Engineer to build AI-native products within our Workforce AI product line. This role is designed for an engineer who builds systems with artificial intelligence at the core, not as an add-on—owning architecture, prompt engineering, model integration, and production-scale delivery. You will work closely with Product, UX, and Platform Engineering teams to deliver scalable, trustworthy AI capabilities that power Cornerstone’s workforce intelligence solutions. In this role, you will... 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.
Requirements
- 8–10 years of professional software engineering experience.
- Strong hands-on experience with Java and/or Python.
- Proven experience delivering AI/ML or Generative AI systems in production.
- Hands-on expertise in prompt engineering and prompt optimization for LLM-powered applications.
- Solid experience with AWS and cloud-native system design.
- Strong working knowledge of SQL and NoSQL databases.
- Ability to design systems that balance AI quality, scalability, latency, and cost.
Nice To Haves
- Experience with LLMs, RAG architectures, vector databases, and structured output enforcement.
- Familiarity with MLOps practices (model versioning, monitoring, evaluation).
- Experience designing AI-powered user experiences in partnership with UX teams.
- Background in enterprise SaaS or workforce/HR technology.
- Experience taking AI products from concept to production.
Responsibilities
- 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.
- 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.
- 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.
- 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.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
