AI Engineer

Salary: $7,000 – $8,500 per month

12 Months Contract

Work Location: 150 Beach Road, The Gateway

Mon - Fri, 9am to 6pm

Overview

We are seeking an AI Engineer to build production AI capabilities for an enterprise HR platform on Microsoft Azure. You will develop Python-based AI services that enable employees, managers and HR teams to complete tasks through natural language, voice and interactive workspaces, reducing manual data entry while preserving validation and human oversight.

You will own AI orchestration, agent tools, knowledge retrieval and evaluation, working with the Technical Lead, Full Stack Engineer, UI/UX Engineer and Product Owner to deliver complete HR journeys across the platform.

Responsibilities

AI services and agent orchestration

• Build Python/FastAPI AI services using Azure OpenAI/OpenAI models. Implement intent recognition, entity extraction, agent routing, conversation context and a versioned tool registry.
• Develop workflows that clarify missing information, prepare structured actions, obtain required approvals and invoke authorised HR APIs. Implement state persistence, safe retries, idempotency and recovery for multi-step tasks.
• Keep AI orchestration within the AI service layer and integrate through the thin Python gateway. Use validated domain services for business rules, calculations and transaction execution.

Knowledge retrieval and data integration

• Build retrieval-augmented generation (RAG) pipelines for HR policies and documents, including ingestion, extraction, chunking, embeddings, search, citations and document refresh.
• Apply tenant, role and document permissions before retrieval and tool execution. Integrate with governed APIs and SQL database in Microsoft Fabric; support analytics through OneLake, semantic models and Power BI.

Conversational and dynamic user experiences

• Integrate text and speech experiences with the frontend team, including streaming, interruptions, session continuity and accessible text alternatives. Connect speech output and timing to avatar components.
• Produce schema-validated UI instructions for approved React components, enabling contextual dashboards, previews, confirmations and explanations of completed actions.

AI safety and evaluation

• Implement prompt-injection protection, sensitive-data handling, output validation and escalation when evidence is insufficient. Record source references, tool actions and concise explanations in audit trails.
• Build representative evaluation datasets and automated regression tests. Measure grounded answer quality, tool selection, task completion, permission enforcement, bias, latency and cost per completed task.

AI responsibilities across HR modules

• Develop the following capabilities with HR subject-matter experts and application engineers. Prioritise delivery through the agreed roadmap and validate each workflow against its acceptance criteria.

Capabilities shared across modules

• Integrate AI actions with tenant context, workflow, notifications, document management, audit, licensing, entitlements and usage quotas. Support governed HR analytics and permission-aware dashboards.
• Apply feature controls and approved integration tools consistently across user roles.

Production delivery and collaboration

• Package AI services with Docker and deploy through CI/CD to the selected Azure runtime. Maintain versioned prompts, models, tools and evaluation results, with controlled release and rollback.
• Integrate with Entra identity, API Management, secure secrets and application monitoring. Apply token budgets, usage metering, timeout limits and trace correlation across services.
• Support UAT, incident diagnosis and customer deployment readiness. Document AI behaviour and limitations, review code, guide junior engineers and work with HR specialists to improve evaluations.

Requirements

• Degree or diploma in a relevant technical field, or equivalent practical experience.
• At least 3 years of software or AI engineering experience, with strong hands-on Python development and evidence of delivering AI-enabled applications into production.
• Practical experience building and operating applications on Microsoft Azure, including Azure OpenAI or equivalent model integration, deployment, monitoring and secure access.
• Strong Python, FastAPI, asynchronous programming, REST APIs, structured output validation and automated testing skills.
• Experience with LLM tool calling, agent workflows, prompt design, conversation state, RAG, embeddings and retrieval evaluation, including handling failures and ambiguous requests.
• Solid SQL and data-modelling knowledge, with experience accessing enterprise data through controlled APIs or relational databases. Understand tenant isolation and role-based permissions.
• Ability to evaluate AI quality systematically, investigate production problems and balance accuracy, response time and operating cost. Comfortable with Git, Docker and CI/CD.
• Clear communication, sound delivery estimates and effective collaboration with application engineers, designers and business users.

Preferred experience

• SQL database in Microsoft Fabric, OneLake, Power BI, Azure AI Search, speech services or document extraction.
• Agent orchestration frameworks such as LangGraph or Semantic Kernel; React/TypeScript integration, streaming APIs or voice and avatar interfaces.
• HR, payroll, recruitment or other enterprise workflow platforms; explainable decision support, fairness evaluation and sensitive employee data handling.
• Customer-hosted Azure deployments, infrastructure as code, AI usage metering, or integration with existing C#/.NET services.

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