About Spark Hire

Spark Hire helps organizations improve the way they hire through modern interviewing, assessment, and talent acquisition technology. Our products support candidates, recruiters, interviewers, hiring managers, and company leaders across more than 7,000 customers and millions of candidate interactions.

As we expand the role of AI across our platforms, we’re looking for an AI Engineer to help us build practical, reliable, and high-impact AI features that solve real customer problems.

About the Role

The AI Engineer will join Spark Hire’s AI and Analytics team and report to the Product Lead for AI and Analytics. This person will work closely with product, engineering, BI/data, and cross-functional teams to design, build, test, and deploy AI-powered applications, tools, and services across Spark Hire’s products.

This role will focus primarily on applied AI: large language models, retrieval systems, automation workflows, data-driven intelligence, and emerging modalities such as speech and multimodal AI. The work will span candidate-facing experiences as well as tools for recruiters, interviewers, hiring managers, and company leaders.

This is a strategic role with broad product exposure and the opportunity to help shape how AI is used across Spark Hire’s platforms.

Why This Role Matters

AI is a major part of Spark Hire’s product strategy. In this role, you’ll help build features that improve the hiring experience for candidates, recruiters, interviewers, hiring managers, and company leaders.

Your work will support strategic product initiatives, reach users across Spark Hire’s platforms, and help define how AI creates meaningful value in the hiring process.

• Design, develop, and deploy AI-powered applications, tools, and services across Spark Hire’s products.
• Develop and maintain retrieval-augmented generation systems, AI agents, model evaluation pipelines, and automation workflows.
• Prototype new AI features quickly and turn successful prototypes into maintainable production systems.
• Partner with product and engineering teams to translate user needs and business goals into practical technical solutions.
• Evaluate and improve AI systems across quality, reliability, latency, cost, safety, and user experience.
• Improve AI outputs through prompt engineering, model selection, data preparation, fine-tuning, and system design.
• Implement testing, monitoring, and quality controls for AI-powered features.
• Ensure AI systems are secure, ethical, compliant, and aligned with company policies.
• Stay current with AI tools, frameworks, models, and best practices.

What We’re Looking For

• 3+ years of experience building AI, including LLM-powered features in a professional software environment.
• Bachelor’s degree in Computer Science, Engineering, or related field.
• Strong programming skills in Python and experience with modern software development practices.
• Hands-on experience with LLM APIs, embeddings, prompt engineering, AI workflows, and model evaluation.
• Experience building APIs, backend services, data pipelines, or production software systems.
• Strong understanding of AI application architecture, including how to design reliable, testable, and maintainable AI systems.
• Ability to move from prototype to production while accounting for edge cases, performance, cost, privacy, and user trust.
• Strong problem-solving skills, attention to detail, and sound technical judgment.
• Excellent communication and collaboration skills.

Nice to Have

• Experience with MLOps, CI/CD, observability, automated testing, or model monitoring.
• Familiarity with fine-tuning, synthetic data generation, vector databases, or model evaluation frameworks.
• Experience building AI agents, copilots, chatbots, recommendation systems, or workflow automation tools.
• Experience with speech, transcription, speech-to-text, text-to-speech, speech-to-speech, or multimodal AI.
• Familiarity with AWS infrastructure.
• Knowledge of data privacy, security, governance, and responsible AI practices.
• Experience in HR tech, recruiting, interviewing, assessment, workflow automation, or SaaS products.