Applied AI Engineer

Location: London, England, United Kingdom; hybrid

Company

hirify.global builds AI-native enterprise software for asset management, operations and critical services, combining LLMs, agentic AI and cloud-native technologies.

What you will do

• Build and curate ontologies, knowledge graphs, semantic layers and grounding infrastructure for AI agents.
• Design MCP servers over product business objects, including capability modelling, discoverability, versioning and backward compatibility.
• Build secure agent write paths, skills routing, control planes, authentication, entitlements, telemetry, metering and injection resistance.
• Develop retrieval, embeddings, vector database, hybrid search, memory and indexing systems that keep agent outputs accurate and traceable.
• Create evaluation harnesses, prototypes and proofs of concept, and establish testing, observability, monitoring, governance, security and operational practices.
• Contribute to technical design and reviews, support colleagues, and represent the work through customer engagements, demonstrations, industry events and partner collaboration.

Requirements

• Demonstrable, hands-on experience designing, building and shipping production AI applications.
• Production experience building and operating enterprise systems, with depth in distributed systems, cloud-native architectures, API and schema design, event-driven systems, security, observability and CI/CD.
• Strong programming skills in a modern backend language.
• Experience delivering LLM-based AI systems, RAG, agentic workflows and orchestration frameworks, including tool use, function calling, workflow orchestration and autonomous or multi-agent architectures.
• Deep hands-on expertise in knowledge graphs and semantic modelling, including ontology design, taxonomy and controlled vocabularies, entity resolution, schema evolution, versioning, embeddings, vector databases and grounding strategies.
• Experience with experimentation, benchmarking, prompt engineering, tracing, quality measurement and agent tuning.
• Ability to integrate enterprise applications, business processes, workflows and data platforms, and to work with domain experts to convert tacit knowledge into explicit machine-usable models.
• Depth in either tool-surface and agent-runtime engineering, including MCP servers and capability governance, or enterprise platform engineering with Oracle PL/SQL, OData and metadata-driven systems.

Nice to have

• Experience with Semantic Kernel, Microsoft Agent Framework, LangGraph, AutoGen, PydanticAI, OpenAI Agents SDK or CrewAI.
• Experience building reusable AI platforms, MCP ecosystems or shared engineering capabilities.
• Experience with Docker, Kubernetes and hyperscale cloud platforms such as Azure, AWS or GCP.
• Reverse-engineering or interpreter experience and token-efficient agent design.
• Experience in enterprise asset management, service management, manufacturing, supply chain, aerospace and defence, energy, telecommunications, construction or industrial AI.
• Contributions to open-source projects, technical communities, conferences, publications or standards.

Culture & Benefits

• Full-time employment in a global, diverse environment focused on collaboration, innovation, sustainability and positive impact.
• Hybrid working with a balance of remote and in-office work, including in-person community interaction.
• Work within a billion-dollar enterprise software company with more than 6,000 employees across all continents.