AI Platform Engineer, Agentic Interfaces

Location: Staines-upon-Thames, England, United Kingdom; hybrid work opportunities

Company

hirify.global develops cloud-based enterprise software for asset management, operations, and critical services, with AI-native products for large organisations.

What you will do

• Design and build MCP servers over product business objects, including capability modelling, discoverability, versioning, and backward compatibility.
• Develop safe agent write paths for changing customer operational data.
• Build semantic and skills layers using ontologies, knowledge graphs, routing, and operation sequencing.
• Implement the control plane for authentication, entitlements, agent identity, telemetry, metering, injection resistance, and deny-by-default security.
• Develop evaluation harnesses, prototypes, and proofs of concept for production AI systems.
• Establish practices for testing, observability, monitoring, governance, security, and operational excellence while contributing to technical reviews and customer engagements.

Requirements

• Production experience building and operating enterprise systems using distributed systems, cloud-native architectures, APIs, schemas, event-driven systems, security, observability, and CI/CD.
• Strong programming skills in a modern backend language.
• Hands-on experience delivering AI systems based on LLMs, RAG, agentic workflows, orchestration, tool use, function calling, and autonomous or multi-agent architectures.
• Experience with evaluation, experimentation, benchmarking, prompt engineering, tracing, quality measurement, and agent tuning.
• Ability to integrate enterprise applications, business processes, workflows, and data platforms.
• Depth in tool-surface and agent-runtime engineering, knowledge graphs and semantic modelling, or enterprise platforms such as Oracle PL/SQL and OData.

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.
• Docker, Kubernetes, and experience with Azure, AWS, GCP, or another hyperscale cloud platform.
• Experience with reverse engineering, interpreters, token-efficient agent design, or relevant enterprise software domains.
• Open-source, technical community, conference, publication, or standards contributions.

Culture & Benefits

• Hybrid work opportunities designed to support flexibility and inclusive workplace experiences.
• International environment with collaboration across a global organisation.
• Work focused on sustainability, enterprise-scale innovation, and practical customer impact.