AI Engineer

Position Overview

We build AI Agents on an internal Agentic AI platform. The platform supports creating and configuring agents, connecting capabilities via MCP, and enriching agent responses using a file-based knowledge base with built‑in document and data RAG capabilities. We focus on building high business value, production‑ready agents, integrations, and evaluation workflows.

We are looking for a strong mid‑level AI Engineer with a hybrid profile—someone who can both build production‑ready AI solutions and lead business‑facing conversations to identify, qualify, and shape high‑value use cases. You will design and build AI Agents on our internal Agentic AI platform, develop MCP servers, engineer prompts and agentic workflows, and work directly with business stakeholders to extract requirements, guide business case development, and assess the strategic value of proposed AI use cases.

Key Tasks and Responsibilities

Business Engagement & Use Case Development

• Lead structured discovery sessions with business stakeholders to extract requirements and map existing processes
• Assess and qualify inbound AI use case requests—evaluating feasibility, complexity, and business value
• Guide business teams through the process of building a business case for agentic AI initiatives
• Facilitate workshops and conversations to translate business problems into well‑defined AI solution briefs
• Act as the bridge between business and engineering—communicating technical constraints and possibilities in accessible business language
• Collaborate with business stakeholders to gather requirements and translate business processes into agent workflows
• Design agent conversation flows and user experiences that align with business objectives, and iterate based on user feedback and business success metrics

AI Engineering

• Create and configure new AI Agents on our Agentic AI platform
• Design, test, and iterate agent instructions/prompts (context engineering) to ensure correct and consistent behaviour
• Connect and configure tools via MCP (define tool contracts, validate behaviour, troubleshoot failures)
• Build new MCP servers when needed (wrap APIs/flows into tools with proper auth, error handling, and logging)
• Design end‑to‑end agentic workflows incorporating analytics pipelines and AI models
• Upload, organise, and maintain files in an agent knowledge base to improve grounding and retrieval quality
• Create and maintain search indexes for file corpora when required (manual index setup and refresh process)
• Set up and run evaluations (offline test sets, regression checks, metrics tracking) using MLflow

Requirements

Business & Communication Skills

• Strong communication skills with the ability to lead business conversations, run discovery workshops, and translate requirements into technical specifications
• Experience in business analysis, requirements gathering, or customer‑facing technical roles
• Ability to assess the business value and feasibility of AI use cases, including ROI framing and prioritisation
• Ability to think from the end‑user perspective and optimise agent UX for business outcomes
• Comfortable facilitating workshops and leading conversations with non‑technical stakeholders

AI Engineering

• 3+ years of professional software engineering experience (backend focus; Python preferred)
• 2+ years building LLM‑powered applications, including AI agents (tool use, RAG/knowledge base grounding)
• Solid understanding of LLMs and their behaviour (tokens/context windows, prompting patterns, hallucinations & grounding, latency/cost trade‑offs)
• Strong experience with prompt/instruction design and iteration (context engineering) and debugging agent behaviour
• Solid understanding of agent architectures (planning, tool execution, memory/context, retrieval grounding, safety/guardrails) with hands‑on delivery experience
• Hands‑on experience integrating external systems and tools via MCP (connecting tools, designing/implementing MCP servers)
• Experience implementing secure integrations using OAuth 2.0 / OIDC and understanding identity concepts such as Azure Entra ID (apps, tenants, scopes/roles, consent)
• Solid software engineering fundamentals: Git, code reviews, testing, logging/monitoring, performance‑aware development
• Good spoken English and ability to work in a highly integrated Agile team

Nice to Have

• Experience with one cloud provider (preferably Azure / AWS / GCP) for deploying or operating services
• Experience using an agentic framework (LangChain, Semantic Kernel, Autogen, CrewAI, or similar)
• Experience with search indexing/retrieval systems (schema design, ingestion pipelines, index refresh automation)
• Familiarity with containerisation (Docker) and basic CI/CD practices for backend services
• Exposure to AI value frameworks or benefit realisation methodologies
• Experience working in a Centre of Excellence (CoE), innovation, or transformation function
• Familiarity with AI governance considerations when assessing use cases (data privacy, risk, compliance)
• Experience with MCP server development from scratch (not just configuration)

What CRH Offers You

• A culture that values opportunity for growth, development, and internal promotion
• Highly competitive salary package
• Comprehensive secondary benefits
• Significant contribution to your pension plan
• Health and wellness programs, including an on‑site gym and fitness classes
• Excellent opportunities to develop and progress with a global organization

Legal & EEO Statements

CRH is an equal opportunity employer. We are committed to creating an inclusive work environment for all employees and actively encourage applications from all sectors of the community.

Benefits/perks listed above may vary depending on the nature of the employment with CRH and the country where you work.

#J-18808-Ljbffr