Applied AI Engineer
Skills
Computer ScienceApplication EngineeringBusiness IntelligenceContextEasily AdaptableOptimizationSilo
What the job involves
The main requirements, responsibilities and hiring steps.
Requirements
- Bachelor's degree in Computer Science Engineering or related field or equivalent practical experience
- 7+ years of software engineering experience with ML or LLM-powered features shipped to production and quality owned
- Deep knowledge of LLM application engineering including prompting structured outputs retrieval context assembly and agentic workflows
- Experience with evaluation methods including golden datasets offline harnesses online monitoring and north-star metrics
- Strong understanding of retrieval and embeddings including vector search semantic retrieval and label flywheels
- Strong Python and/or TypeScript skills with comfort across modern backend systems like Node.js NestJS MongoDB and message queues
- Fluent use of AI coding tools in daily work with clear opinions on where they help and where they do not
- Proven ownership mindset with early action initiative and strong customer focus
- Excellent analytical problem-solving communication and collaboration skills
Nice to have
- Opinionated
- Customer-minded
- Cross-functional
- Analytical
- Proactive
Day to day
- Own AI features end-to-end from problem statement to GA, including initiative classification narratives work codes daily themes compliance and vision extraction.
- Build robust evaluation systems with golden datasets north-star metrics and online monitoring to prove feature quality and reliability.
- Improve semantic retrieval context assembly prompt optimization and per-customer generation while collaborating closely with product designers and engineers.