Applied AI Engineer

Build the intelligence behind the experience: the session and memory model retrieval across our own estate and the documents that run it the agentic flows that carry out multi-step work and the evaluation that tells us whether any of it is right. 

What you will do 

• Build the session and context spine: persistence resumption hand-over with the reasoning trail intact and context resolved from a persons identity and entitlements. 

• Build retrieval and grounding across structured records and documents at a cost and latency the product can afford. 

• Build document intelligence over manuals engineering drawings certification directives and contracts extracted and citable because for many of our customers those carry as much operational truth as the databases. 

• Build the agentic flow runtime: multi-step work with tools and the rules that decide when a human is asked rather than told. 

• Handle speech and images as first-class input alongside text so the same request works dictated in a plant room or photographed at an asset. 

• Build the evaluation harness and treat it as the gate on every claim we make about autonomy. 

• Build the language interface over our scheduling and optimisation engines expressing trade-offs in the customers own terms. 

• Build the security layer with our security team: resistance to prompt injection personal data handling guardrails audit and data residency. 

Qualifications :

• Experience with S2S integration preferably using technologies such as n8n or Temporal or alternatively MuleSoft Apache Camel or Boomi.
• Experience with Go and Python.
• Experience building multi-tenant SaaS solutions.
• Experience building and scaling AI-native products and applications.
• Experience with production-grade GenAI solutions including RAG pipelines (hybrid retrieval embeddings) and agentic systems (agent orchestration tool usage).
• Experience with AI frameworks and tooling such as Pydantic AI LangChain and MCP.
• Experience with MCP development and plan-based agentic software development.
• Experience with DevOps and cloud-native infrastructure including Docker Kubernetes CNCF technologies and CI/CD pipelines.
• Experience with API gateways and API products preferably with platforms such as Kong or Tyk.
• Preferably experience optimizing AI services for latency and cost.
• Preferably experience with specification-driven development.
• Passionate about and eager to adopt new technologies.
• Up to date with the latest developments in GenAI and AI-based software development.

Additional Information :

Remote Work :

No

Employment Type :

Full-time