AI Engineer
Listed on 2026-06-05
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Software Development
AI Engineer, Cloud Engineer - Software
MeetUnit4 . With over 40 years of heritage, we’re an agile, fast growing, Cloud company that is on a mission to redefine Enterprise Resource Planning (ERP) for mid-market people-centric organisations.
With our innovative, self-driving, adaptive and intuitive software, our customers can spend more time on meaningful high-value work.
At the heart of what we do lies a simple yet profound purpose:
Improve how people work by focusing on what truly matters. — A powerful statement that enables different priorities for different people.
We’re shaping
how work should feel
, and we empower our people by providing them with the right tools to achieve the autonomy they need - it's what makes us unique.
We're looking for an AI Engineer to design, build, and operate production‑grade AI and Generative AI solutions across the company. This is a hands‑on engineering role: you'll turn architecture and business requirements into working, scalable systems - including LLM applications, AI agents, RAG pipelines, and integrations with our enterprise platforms. The role has a strong emphasis on Microsoft Azure and the Microsoft Copilot ecosystem, which are our primary enterprise platforms.
Key Responsibilities- Design and implement AI‑driven solutions that automate business processes, reduce manual effort, and improve service delivery across the organization.
- Build production‑grade GenAI applications — LLM‑powered features, AI agents, copilots, and orchestration layers — translating architectural patterns into working code.
- Contribute to PoCs and pilots, rapidly prototyping new capabilities and bringing them to a production‑ready state when validated.
- Develop and integrate AI agents and multi‑agent systems using established orchestration frameworks.
- Build APIs and microservices that expose AI capabilities to internal teams and products, following architecture and security standards.
- Integrate AI solutions with enterprise platforms (e.g., CRM, ERP, ITSM, data warehouse, identity, observability stack) via APIs, events, and connectors.
- Ensure designs support scale, reliability, and change management — versioning, backward compatibility, and clear contracts.
- Contribute to responsible AI practices and internal policy development by translating principles into engineering standards, reusable patterns, and reference implementations.
- Implement governance and security controls in code, including: data classification and PII handling, prompt injection defences and content filtering, audit logging and traceability, and RBAC/least‑privilege access patterns.
- 3+ years of professional software engineering experience, with 1–2 years building and shipping AI/ML or Generative AI solutions in production.
- Proven track record of delivering AI features that run in production with real users.
- Hands‑on experience in enterprise environments: security, compliance, integrations, and scale.
- LLMs & GenAI:deep practical experience with foundation models, prompt engineering, tool/function calling, structured outputs, and context management.
- Agents & orchestration:hands‑on experience building agents, copilots, or multi‑agent workflows.
- Microsoft Azure:deploying and operating AI workloads on Azure — specifically Azure OpenAI Service, Azure AI Foundry, Azure AI Search, and related services.
- Microsoft Copilot ecosystem: extending or integrating Microsoft 365 Copilot; building custom copilots and agents with Microsoft Copilot Studio.
- Python:strong production‑quality Python — typing, testing, packaging, and async patterns.
- APIs & services:
REST and/or gRPC; event‑driven patterns; API design and versioning. - MLOps fundamentals:experiment tracking, model and prompt versioning, automated evaluation, and monitoring of AI systems in production.
- Multi‑model experience:familiarity with working across LLM providers (e.g., Azure OpenAI, third‑party models via Azure AI Foundry) and adapting to provider‑specific patterns such as tool use, structured outputs, and long‑context handling.
- Experience with embedded/on‑platform AI tooling such as Service Now Now Assist or similar ITSM AI capabilities.
- Strong communication skills — able to explain technical decisions…
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