Senior AI Engineer, Agentic Systems

RESPONSIBILITIES:

• Develop and continuously improve the tools that connect agents to critical information sources, including web access, semantic and hybrid retrieval, structured-data querying, internal APIs, and knowledge graphs.
• Design, implement, and evaluate agentic workflows and multi-agent systems that effectively balance exploration and exploitation, accuracy and latency, and autonomy and control.
• Define evaluation frameworks and metrics for retrieval quality, agent performance, factual accuracy, and business relevance.
• Partner closely with Research, Product, and Engineering to rapidly prototype, test, and refine new capabilities through short feedback loops.
• Take solutions from prototype to production, including API development, CI/CD pipelines using GitHub Actions, and Kubernetes deployments across multiple environments using core AWS services such as RDS, EKS, and S3.
• Own the full lifecycle of the systems and services you build—from architecture and implementation through deployment, adoption, monitoring, maintenance, and continuous improvement.

QUALIFICATIONS:

• Interest in or experience with global security, financial crime, sanctions, export controls, or related domains.
• 5+ years of professional experience in AI engineering, data science, software engineering, data engineering, or a closely related role.
• Strong proficiency in Python and SQL.
• Proven experience building and operating RAG pipelines and agentic systems in production.
• Hands-on expertise in search and retrieval, including BM25, vector search, hybrid retrieval, reranking, and retrieval evaluation.
• Experience designing APIs and deploying containerized services using Docker and Kubernetes.
• Demonstrated track record of rapidly prototyping agentic workflows that solve real user or business problems, with the production experience to make pragmatic decisions about what to harden, scale, or discard.
• Strong product judgment and ownership, with the ability to translate ambiguous business requirements into prototypes, define a technical roadmap, and independently drive execution.
• Bonus: Experience with graph-aware retrieval, graph databases, or integrating knowledge-graph outputs into search and agentic systems.
• This is you if you have a track record of building autonomous systems that drive deep dive investigations into a topic – orchestrating multi-agent workflows, integrating diverse data sources, and building self-correcting evaluation loops that aren't afraid to test hypotheses and fail gracefully.
• This is you if you're comfortable owning infrastructure end-to-end — deploying a database, designing a schema, shipping an API — without a dedicated platform or DevOps team.*

ABOUT KHARON: