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Senior AI Engineer

quantum
London, GBR
Full-time
Hybrid
Discovered 1 weeks ago
Software engineeringMulti-agent systemsGenerative AIAgentic workflowsLangGraphAutoGen
Free

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Software engineeringMulti-agent systemsGenerative AI
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About Quantum

Quantum connects global brands with high-intent consumers through data-driven affiliate marketing and digital comparison services.

The company uses in-house technology, analytics, and a compliance-first approach to support growth in regulated and high-growth sectors.

The Role

Quantum is seeking an experienced Senior AI Engineer to design, develop, and deploy AI systems for personalized advertising, customer journey analytics, audience segmentation, and real-time bidding.

The role works with BI, data engineering, and product teams to build scalable AI solutions for marketing and advertising challenges.

The infrastructure is powered by Google Cloud Platform.

Key Responsibilities

  • Design, build, and deploy scalable multi-agent systems and generative AI features for ad targeting, user segmentation, and content personalization.
  • Research agentic design patterns such as planning, reflection, and tool usage using frameworks including LangGraph, AutoGen, or CrewAI.
  • Translate ambiguous business objectives into agent personas, tool definitions, and behavioral boundaries.
  • Monitor production systems using agent-specific metrics including token efficiency, execution loops, and tool-calling accuracy.
  • Maintain data security, model explainability, and safeguards against prompt injection and unintended tool execution under GDPR and CCPA.
  • Mentor junior engineers and promote best practices in agent programming, prompt engineering, model evaluation, and cloud infrastructure.

About You

  • Experience in software engineering, ideally in Ad Tech, Mar Tech, or another complex, high-scale environment.
  • Experience building multi-agent or single-agent architectures with API or MCP integrations.
  • Understanding of supervised, unsupervised, and reinforcement learning methods, foundation models, and prompt engineering.
  • Practical experience with GCP services or AWS equivalents such as Vertex AI, BigQuery ML, Dataflow, AI Platform Pipelines, or Dataproc.
  • Practical experience with CI/CD for AI or machine learning, model versioning, monitoring, and AI Ops practices.
  • Excellent communication, collaboration, knowledge-sharing, and ambiguity-navigation skills.

Preferred Qualifications

  • Understanding of marketing and advertising concepts including customer lifetime value, attribution modeling, real-time bidding, and audience targeting.
  • Familiarity with Apache Airflow and Kubernetes.

Working Arrangement

  • Hybrid working with three days in the office.

Benefits

  • Benefits include private health care, travel insurance, a company bonus scheme, paid AI subscriptions, training, recognition programs, and an annual company conference.
  • Additional offerings include regular team events, free refreshments, and a recognition and reward scheme.

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