aimlroles

Senior AI Engineer, Agentic Systems

Kharon kharon.com Open · verified Oct 22, 2026
Hybrid London Full-time Senior AI Engineering

At a glance

Senior AI Engineering role at Kharon. London · full-time · £105,000–£120,000 base.

SalaryStated by Kharon
£105,000 – £120,000
Base salary for this role, in GBP per year, as published in the posting.
RoleAI Engineering
SenioritySenior
LocationLondon
WorkplaceHybrid
EmploymentFull-time
Base pay£105,000–£120,000
PostedAug 3, 2026 · 2mo ago
Role brief

aimlroles summary, based on the employer's posting.

What you'll do

  • Build agents that interpret, rank, and act on geopolitical and financial signals
  • Connect agents to web sources, retrieval systems, structured data, internal APIs, and knowledge graphs
  • Create and assess agent workflows, including multiple-agent setups, for accuracy, speed, and controlled autonomy
  • Set measures for retrieval quality, factual accuracy, agent performance, and business relevance
  • Move prototypes into production through APIs, GitHub Actions, Kubernetes, and AWS services, then monitor and improve them

What you bring

  • At least five years in AI, data science, software or data engineering, or a closely related profession
  • Strong Python and SQL skills, plus production experience with RAG pipelines and agent-based systems
  • Practical search expertise spanning BM25, vector and hybrid retrieval, reranking, and retrieval assessment
  • Experience building APIs and deploying Docker-based services on Kubernetes

Who this fits

This suits a senior engineer who can turn unclear needs into prototypes, set technical direction, and carry work through production. You can bring depth in investigative agent workflows or end-to-end platform ownership; strength in both is welcome. The role is based in London and requires three on-site days each week.

From the employer

TL;DR Kharon is seeking a full-time London-based Senior AI Engineer, Agentic Systems.
Location: London, UK Annual Remuneration: £105,000 - £120,000 and discretionary annual bonus Pay Frequency: Monthly Probationary Period: 180 days Work Arrangement: Hybrid, 3-days per week

Build and deploy AI agents that can interpret, prioritize, and act on information related to geopolitical and financial signals. This includes:
  • 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.

  • 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.
You don't need to be strong in both tracks below — we're building a small team that covers the full range between them:*

Track A — Research & Investigation Depth
  • 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.
  • Hands-on expertise in search and retrieval, including BM25, vector search, hybrid retrieval, reranking, and retrieval evaluation.
Track B — Platform & Systems Self-Sufficiency
  • 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.*
  • Experience designing APIs and deploying containerized services using Docker and Kubernetes.

Bonus: Experience with graph-aware retrieval, graph databases, or integrating knowledge-graph outputs into search and agentic systems — strength in both tracks above is also a plus.