Agentic AI Engineer

City of London

£90,000 +

‍As an Agentic AI Engineer, you’ll design and build intelligent systems that think, reason and act.

Solve hard problems at scale, integrate data, AI and automation to create self-improving systems that deliver measurable business value.

You’ll work with as part of a Data and AI hands-on engineering team that’s turning Agentic AI from concept to production reality.

The role:
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• Lead solution engineering for agentic systems that become core to client transformation programmes
• Co-create solutions that move enterprises from AI-enabled to AI-native
• Contribute to a global framework defining how intelligent systems are built, governed and scaled
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• ‍Design and build agentic systems that combine reasoning, planning and action across complex enterprise environments

• Engineer modular components within the Agentic AI Framework
• Build and deploy scalable solutions across multi-cloud environments using containerisation, microservices and event-driven design
• Translate client challenges into engineered systems that reason, learn and adapt – improving efficiency, resilience and decision-making
• Bridge AI and data architecture to ensure agents are grounded in solid data foundations, scalable pipelines and secure governance
• Automate end-to-end with CI/CD pipelines, observability and responsible-AI guardrails
• Collaborate and mentor across disciplines to accelerate delivery and strengthen technical excellence
• Deliver measurable outcomes that move clients from AI-enabled experiments to production-grade AI-native enterprise

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‍‍We need:

• Strong coding skills in Python and experience with agentic and LLM framework
• Hands-on experience in data engineering and architecture – APIs, streaming, ETL or data mesh principles
• Ability to work across multi-cloud and data platform ecosystems (AWS, Azure, GCP, Databricks, Snowflake, Fabric, Elastic)
• Familiarity with vector databases, knowledge graphs or temporal data models
• Understanding of LLM orchestration, RAG pipelines, tool-use and agent frameworks
  
  

• Degree or equivalent practical experience in computer science, data engineering, AI or a related technical field
• Proven hands-on experience in Agentic AI or GenAI engineering
• Strong programming fluency in Phyton
• Solid understanding of data and software architecture patterns such as microservices, message brokers, streaming and event driven design
• Demonstrated ability to deliver production grade AI solutions that integrate data pipelines, models and orchestration logic across multi-cloud or hybrid environments
  

• Certifications across AWS, Azure or Google Cloud
• Proven experience with data and AI platforms such as Databricks, Snowflake, Fabric or Elastic
• Prior involvement in digital transformation or AI native product development within enterprise settings