Job Summary

An AI-native B2B sales platform that helps companies find high-intent buyers by analyzing hundreds of buying signals across multiple sources, identifying the reason an account is ready to buy, and turning that intelligence into personalized outreach, account research and deal-closure workflows.

Responsibilities

- Own the intelligence layer. Build RAG and retrieval systems that pull in data from multiple sources to make every AI output relevant and grounded in real context.
- Build AI agents and workflows - research agents, enrichment agents, follow-up sequencing agents that operate reliably at scale without human intervention.
- Build the evaluation framework that measures output quality before anything reaches real prospects.
- Define what "good" means and build the infrastructure to measure it consistently.
- Make the AI meaningfully better, measurably, every week.
- Make measurable improvements to retrieval quality or agent reliability.
- Diagnose the biggest AI quality gaps and create a prioritized plan to close them.
- Stay current with new model releases, new frameworks, and new research.
- Evaluate and make decisions on the right retrieval strategy, the right eval metric, the right model for a given task.




- Work on backend or frontend that work with the AI backend when required.
- We're looking for an AI Engineer to build and own production-grade AI systems, including RAG pipelines, AI agents, production chatbots, and evaluation frameworks.
- You'll work with frontier models, vector databases, and LangGraph to improve retrieval quality, agent reliability, and overall AI performance.
- The ideal candidate has 2-3+ years of hands-on production AI/ML experience, strong system design skills, and deep expertise in RAG and AI evaluation.
- This is a high-ownership role where you'll be expected to ship, measure, iterate, and make meaningful improvements to AI quality every week.

Qualifications

- 2-3+ years of hands-on production AI/ML experience.
- Solid system design skills.
- Deep expertise in RAG and AI evaluation.

Skills

- RAG pipelines
- AI agents
- production-grade AI systems
- evaluation frameworks
- frontier models
- vector databases
- LangGraph
- system design
- AI/ML experience

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

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